CN117094177B - Track generation method and system based on solenopsis invicta prevention and control - Google Patents
Track generation method and system based on solenopsis invicta prevention and control Download PDFInfo
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Abstract
The invention relates to the technical field of prevention and control of solenopsis invicta, in particular to a track generation method and system based on prevention and control of solenopsis invicta. The method comprises the following steps: establishing migration simulation coordinates by using a GIS technology and solenopsis invicta image data, and performing migration path simulation mapping processing on the migration simulation coordinates to generate simulated migration path data; carrying out migration path data prediction on the simulated migration path data to generate migration path prediction data; extracting dangerous migration path prediction data from migration path prediction data to obtain dangerous migration path prediction data; carrying out migration path design according to the dangerous migration path prediction data to generate migration path data; performing red fire ant prevention and control track design according to the migration path data to generate red fire ant prevention and control track data; and carrying out real-time optimization processing on the red ant prevention and control track data so as to generate optimized red ant prevention and control track data. The invention realizes the precise prevention and control of the solenopsis invicta.
Description
Technical Field
The invention relates to the technical field of prevention and control of solenopsis invicta, in particular to a track generation method and system based on prevention and control of solenopsis invicta.
Background
The prevention and control of solenopsis invicta is of great importance, because the invasive ant species pose a serious threat to humans, ecosystems and agriculture, solenopsis invicta adversely affects the ecosystems, they are omnivorous predators, damage other insect populations, disturb the food chain, and destroy local biodiversity. In addition, they feed on large scale cultivated lands, orchards and farmlands, causing significant losses to the agricultural economy. Therefore, the prevention and control of solenopsis invicta are to protect human health, maintain ecological balance, and ensure agricultural sustainability and economic benefit. However, the conventional track generation method for controlling the solenopsis invicta relies on static ecological data, and cannot adapt to the changing situation in time, so that the activity of the solenopsis invicta cannot be accurately predicted, and the migration mode and the time sequence of the solenopsis invicta are not considered, so that the behavior of the solenopsis invicta is difficult to accurately predict.
Disclosure of Invention
Based on the above, the invention provides a track generation method and system based on solenopsis invicta prevention and control, so as to solve at least one of the above technical problems.
In order to achieve the above purpose, a track generation method based on solenopsis invicta prevention and control comprises the following steps:
Step S1: forest environment data acquisition is carried out by utilizing a GIS technology, and forest environment data is generated; carrying out real-time acquisition on the solenopsis invicta image data of the target analysis area by using electronic monitoring equipment to generate solenopsis invicta image data;
step S2: establishing migration simulation coordinates by using a GIS technology and solenopsis invicta image data, and performing migration path simulation mapping processing on the migration simulation coordinates to generate simulated migration path data;
step S3: performing time sequence division processing on the simulated migration path data to generate time sequence migration path data; performing migration path data prediction on the time sequence migration path data by using a long-short memory neural network algorithm to generate migration path prediction data;
step S4: acquiring an ecological sensitivity report; acquiring ecological activity range data by using a GIS technology to generate ecological activity range data; performing abnormal migration path prediction extraction on migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data; performing migration path risk assessment on abnormal migration path prediction data according to the ecological sensitivity report, and generating migration path risk grade data; extracting dangerous migration path prediction data from abnormal migration path prediction data according to migration path risk level data to obtain dangerous migration path prediction data;
Step S5: carrying out migration path design according to the dangerous migration path prediction data to generate migration path data; collecting historical solenopsis invicta diffusion data of the ecological activity range data to generate historical solenopsis invicta diffusion data; performing solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data, and generating migration path diffusion data; performing red fire ant prevention and control track design according to the migration path data and the migration path diffusion data to generate red fire ant prevention and control track data;
step S6: and carrying out real-time optimization processing on the red ant prevention and control track data so as to generate optimized red ant prevention and control track data.
According to the invention, forest environment data acquisition is carried out by utilizing a GIS technology, the system can acquire key environment information such as temperature, humidity, topography and the like in real time, the environment of the solenopsis invicta can be accurately understood, the image data of the solenopsis invicta in a target analysis area is acquired in real time by utilizing electronic monitoring equipment, the system acquires instant activity information of the solenopsis invicta, including distribution, quantity, moving paths and the like, and the combination of the data enables the system to accurately grasp the survival condition and behavior of the solenopsis invicta, so that reliable basis is provided for subsequent prevention and control measures, and the prevention and control efficiency and accuracy are improved. The GIS technology is utilized to combine the solenopsis invicta image data to establish migration simulation coordinates, and migration path simulation mapping processing is carried out on the coordinates to generate simulated migration path data, so that migration behaviors of solenopsis invicta can be simulated, movement modes and habits of the solenopsis invicta can be understood in depth, not only can the current position of the solenopsis invicta be tracked, but also possible migration paths of the solenopsis invicta can be predicted, precious information is provided, a solenopsis invicta prevention and control strategy can be formulated more pertinently, and prevention and control accuracy and efficiency are further improved. The simulated migration path data are subjected to time sequence division processing, so that time sequence migration path data are generated, the time sequence migration path data are analyzed and modeled by applying a long and short memory neural network (LSTM) algorithm, migration path prediction data are generated, the actual migration history of solenopsis invicta can be tracked, possible action paths in the future can be predicted, the prevention and control strategy is more intelligent, migration behaviors of the solenopsis invicta can be better dealt with through analysis and prediction of the time sequence data, and the prevention and control efficiency and success rate are improved. By acquiring the ecological sensitivity report, acquiring important information about forest ecological environment, acquiring ecological activity range data by means of GIS technology, forming an ecological activity range data set, extracting abnormal migration paths from migration path prediction data, determining potential risk areas by identifying prediction paths which are inconsistent with the ecological activity range, carrying out risk assessment on the abnormal migration paths according to the ecological sensitivity report, generating risk grade data of the migration paths, analyzing the risk grade data, extracting dangerous migration path prediction data by a system, helping prevention and control personnel to take measures more specifically, protecting the ecological environment from potential threats, improving accuracy and ecological friendliness of red fire ant prevention and control, and integrating ecological factors into prevention and control strategies so that the red fire ant prevention and control strategy is more intelligent and sustainable. According to the dangerous migration path prediction data, the migration path is designed, specific migration path data is generated, prevention and control measures can be planned according to dangerous areas and the red fire ant prediction activity route, pertinence and effectiveness of a prevention and control strategy are improved, historical red fire ant diffusion data acquisition is conducted on ecological activity range data, historical diffusion data are generated, the historical diffusion data are helpful for understanding the behavior mode and trend of past red fire ants, the migration path data and the historical red fire ant diffusion data are analyzed, migration path diffusion data are generated, the propagation mode and speed of the red fire ants can be predicted more accurately, the red fire ant prevention and control track data are generated based on the migration path data and the diffusion data, the prevention and control plan is optimized, the prevention and control track with more pertinence and effectiveness is provided according to migration and diffusion behaviors of the red fire ants, the red fire ants are helped to be controlled more accurately, and influence on ecological environment is reduced. The control track data of the solenopsis invicta is subjected to real-time optimization processing, which means that the system can dynamically adjust the control track according to the latest data and conditions to generate the optimized control track data of the solenopsis invicta, so that the control strategy has higher flexibility and adaptability, and can cope with the changing behavior and new risk area of the solenopsis invicta at any time, thereby improving the real-time performance and efficiency of control, timely adjusting the deployment of control measures through real-time optimization, ensuring that the harm of the solenopsis invicta on ecological environment and agriculture is furthest reduced, and ensuring the success of control work. Therefore, the track generation method based on the prevention and control of the solenopsis invicta not only depends on static ecological data, but also dynamically collects and analyzes relevant data of the solenopsis invicta, and can adapt to the changing situation in time, so that the activity of the solenopsis invicta can be accurately predicted, and the migration mode and the time sequence of the solenopsis invicta are considered, so that the behavior of the solenopsis invicta can be accurately predicted.
Preferably, step S1 comprises the steps of:
step S11: forest environment data acquisition is carried out by utilizing a GIS technology, and forest environment data is generated;
step S12: acquiring solenopsis invicta livability condition data;
step S13: screening a target analysis area of the solenopsis invicta on the basis of the solenopsis invicta livability condition data to generate a target analysis area;
step S14: and (3) carrying out real-time acquisition on the solenopsis invicta image data of the target analysis area by using the electronic monitoring equipment to generate the solenopsis invicta image data.
The invention utilizes the GIS technology to collect forest environment data, generates forest environment data, provides comprehensive data about forest environment, including information such as topography, vegetation, weather and the like, is beneficial to the system to comprehensively know the ecological environment of the prevention and control area, and provides necessary background information for the follow-up solenopsis invicta prevention and control strategy. And the condition data of the solenopsis invicta suitable for survival can be obtained, and conditions of the solenopsis invicta suitable for survival, such as temperature, humidity, food resources and the like, can be known better, so that the life habit and the behavior mode of the solenopsis invicta can be understood better, and a foundation is provided for subsequent target analysis. The forest environment data is screened based on the solenopsis invicta livability condition data to generate the target analysis area, so that the system is helped to determine the possible area of solenopsis invicta activity, the positioning accuracy is improved, excessive monitoring of the whole area is avoided, and resources are saved. The electronic monitoring equipment is utilized to collect the image data of the solenopsis invicta in the target analysis area in real time to generate the image data of the solenopsis invicta, so that real-time and visual data are provided, a system is allowed to track and monitor the distribution and activity conditions of the solenopsis invicta in time, and the real-time performance and accuracy of prevention and control are improved.
Preferably, step S2 comprises the steps of:
step S21: carrying out red fire ant nest node acquisition according to the red fire ant image data to generate red fire ant nest node data;
step S22: carrying out solenopsis invicta migration path acquisition according to the solenopsis invicta image data to generate migration path data;
step S23: and establishing migration simulation coordinates by using a GIS technology and the solenopsis invicta nest node data as central nodes, transmitting migration path data to the migration simulation coordinates for migration path simulation mapping processing, and generating simulation migration path data.
According to the method, the red fire ant nest node acquisition is carried out according to the red fire ant image data, the red fire ant nest node data are generated, nest positions of the red fire ants can be accurately identified and marked, important starting point information is provided for subsequent migration path modeling, and the method is beneficial to more accurately knowing the activity center of the red fire ants. And acquiring the migration paths of the solenopsis invicta according to the image data of the solenopsis invicta, generating migration path data, and acquiring migration behavior data of the solenopsis invicta by monitoring and recording the actual migration paths of the solenopsis invicta, so that migration habits and modes of the solenopsis invicta are more accurately simulated and analyzed. The GIS technology and the solenopsis invicta nest node data are used as central nodes to establish migration simulation coordinates, migration path data are transmitted to the migration simulation coordinates to carry out migration path simulation mapping processing, simulation migration path data are generated, the actual nest nodes are combined with the simulation coordinates to create a virtual environment capable of simulating the migration of the solenopsis invicta, so that a system can simulate and analyze the migration behavior of the solenopsis invicta, and understanding and predicting capacity of a migration mode of the solenopsis invicta are further improved.
Preferably, step S3 comprises the steps of:
step S31: performing time sequence division processing on the simulated migration path data to generate time sequence migration path data;
step S32: establishing a mapping relation of migration path prediction by using a long-short memory neural network algorithm, and generating an initial migration path prediction model;
step S33: carrying out data division processing on the time-series migration path data to respectively generate a time-series migration path training set and a time-series migration path testing set;
step S34: performing model training on the initial migration path prediction model by using a time sequence migration path training set to generate a migration path prediction model;
step S35: and transmitting the time sequence migration path test set to a migration path prediction model to predict migration path data, and generating migration path prediction data.
According to the method, the simulated migration path data are subjected to time sequence division processing, the time sequence migration path data are generated, and the migration path data are divided according to time sequence, so that the system is facilitated to capture the time sequence characteristics of the solenopsis invicta migration, and the time sequence and the accuracy of the migration model are improved. The mapping relation of migration path prediction is established by using a long-short memory neural network algorithm, an initial migration path prediction model is generated, and a deep learning algorithm is introduced, so that the system can better capture a complex mode in time sequence data, and a basic migration path prediction model is established. And carrying out data division processing on the time-series migration path data to respectively generate a time-series migration path training set and a time-series migration path testing set, ensuring that enough data are used for model training and verification, and being beneficial to improving the generalization performance and reliability of a migration path prediction model. Model training is carried out on the initial migration path prediction model by using the time sequence migration path training set, so that a migration path prediction model is generated, and the system can learn the complex relation of time sequence migration data through the training model, so that the accuracy and usability of the prediction model are further improved. The time sequence migration path test set is transmitted to the migration path prediction model to predict migration path data, migration path prediction data are generated, new time sequence migration data can be accurately predicted by using the trained model, valuable prediction information is provided for the migration path of the solenopsis invicta, and the prevention and control strategy can be formulated more accurately.
Preferably, step S4 comprises the steps of:
step S41: acquiring an ecological sensitivity report;
step S42: acquiring ecological activity range data by using a GIS technology to generate ecological activity range data;
step S43: performing abnormal migration path prediction extraction on migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data;
step S44: performing migration path risk assessment calculation on abnormal migration path prediction data by using a migration path risk level algorithm and an ecological sensitivity report to generate migration path risk level data;
step S45: and extracting dangerous migration path prediction data from the abnormal migration path prediction data according to the migration path risk level data so as to obtain dangerous migration path prediction data.
The invention acquires the ecological sensitivity report, can acquire the detailed report about the ecological system of the prevention and control area, comprises the information of vulnerability of the ecological environment, biological diversity, vegetation coverage and the like, and the ecological sensitivity report provides the assessment of the vulnerability of the ecological environment, thereby being beneficial to better understanding the ecological risk and potential influence of the system. The GIS technology is utilized to collect ecological activity range data, and ecological activity range data are generated, so that accurate data related to different ecological systems such as wetlands, forests, farmlands and the like can be obtained, and the system is facilitated to better identify potential ecological sensitive areas and survival conditions of solenopsis invicta. And carrying out abnormal migration path prediction extraction on the migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data, so that a prediction path which is inconsistent with the ecological activity range can be identified, a prevention and control key area is further screened and focused, and redundant monitoring and resource waste are reduced. And carrying out migration path risk assessment calculation on abnormal migration path prediction data by using a migration path risk level algorithm and an ecological sensitivity report to generate migration path risk level data, comprehensively considering the relevance of ecological risk factors and solenopsis invicta migration paths, generating ecological sensitivity-based risk level data, and being beneficial to more pertinently formulating a prevention and control strategy. And extracting dangerous migration path prediction data from the abnormal migration path prediction data according to the migration path risk level data to obtain dangerous migration path prediction data, and identifying the migration path with the highest risk, so that the distribution of prevention and control resources is optimized, the priority attention of a high-risk area is ensured, and the accuracy and the urgency of prevention and control of the solenopsis invicta are improved.
Preferably, the migration path risk level algorithm in step S44 is as follows:
；
in the method, in the process of the invention,expressed as migration path risk level data, < +.>Expressed as the number of risk factors>Denoted as +.>Risk factors,/->Migration path length expressed as abnormal migration path prediction data,/for each of the plurality of blocks>Temperature influence coefficient expressed as physiological sensitivity report, < ->Represented as an abnormal migration pathTemperature data of predictive data, +.>Humidity influence coefficient expressed as physiological sensitivity report, < ->Humidity data expressed as abnormal migration path prediction data,/and/or>Expressed as the number of external risk factors, +.>Denoted as +.>Individual external risk factors,/->Expressed as extra migration path length generated from external risk influencing factors,/for>An anomaly adjustment value expressed as migration path risk level data.
The invention utilizes a migration path risk level algorithm which fully considers the number of risk factorsFirst->Personal risk factor->Migration path length of abnormal migration path prediction data +.>Temperature influence coefficient reported by ecological sensitivity +.>Temperature data of abnormal migration path prediction data +.>Humidity influence coefficient of ecological sensitivity report +. >Humidity data of abnormal migration path prediction data +.>Number of external risk factors->First->Personal external risk influence coefficient->Additional migration path length generated according to external risk influencing factors>And interactions between functions to form a functional relationship:
that is to say,the functional relation can be used for evaluating the risk level of the abnormal migration path prediction data, so that the functional relation is used for carrying out a corresponding prevention and control strategy on the abnormal migration path prediction data with high risk level in the subsequent step. The number of risk factors is used to evaluate the number of internal factors of the risk. These internal factors may include factors related to solenopsis invicta ecology, such as temperature, humidity, food resources, etc., reflecting the complexity and diversity of the internal factors considered by the algorithm; first->The risk influence coefficient reflects that each risk factor has a related weight or influence coefficient, measures the influence degree of each factor on the total risk, and the temperature on the solenopsis invictaThe impact of activity may be more important than humidity, so the corresponding parameter values will be higher; abnormal migration path length, typically expressed in certain distance units, longer paths may increase risk; the temperature influence coefficient of the ecological sensitivity report and the humidity influence coefficient of the ecological sensitivity report respectively represent the influence weights of the temperature and humidity factors in the ecological sensitivity report, so that the algorithm is helped to more accurately consider the influence of different meteorological conditions on the migration path; the temperature data of the abnormal migration path prediction data and the humidity data of the abnormal migration path prediction data are related to the abnormal migration path, and respectively represent the values of the temperature and the humidity, and can be actual measured values obtained from a sensor or meteorological data; the number of external risk influencing factors is used for evaluating the number of factors influenced by external factors, and the external factors may include weather conditions, human activities and the like; first- >Each external risk factor has an associated weight or influence coefficient that measures the extent to which each factor affects the overall risk; additional migration path lengths generated based on external risk influencing factors, such as increased migration path lengths due to bad weather. The functional relationship fully considers a plurality of risk factors, including internal and external factors, and by comprehensively considering the factors, a more comprehensive assessment of migration path risk is provided, so that the potential risk of solenopsis invicta diffusion is reflected more accurately. Abnormality adjustment value +.>And the functional relation is adjusted and corrected, so that the error influence caused by abnormal data or error items is reduced, the migration path risk grade data is generated more accurately, and the accuracy and reliability of migration path risk assessment calculation on abnormal migration path prediction data are improved. Meanwhile, the adjustment value in the formula can be adjusted according to actual conditions and is applied to different abnormal migration path prediction data, so that the flexibility and applicability of the algorithm are improved.
Preferably, step S45 comprises the steps of:
And performing data screening on the migration path risk level data according to a preset migration path risk level threshold, and performing data extraction on abnormal migration path prediction data corresponding to the migration path risk level data when the migration path risk level data is larger than the preset migration path risk level threshold so as to obtain dangerous migration path prediction data.
According to the method, data screening is carried out on migration path risk level data according to the preset migration path risk level threshold, when the migration path risk level data is larger than the preset migration path risk level threshold, data extraction is carried out on abnormal migration path prediction data corresponding to the migration path risk level data so as to obtain dangerous migration path prediction data, and the system can automatically screen out migration paths with higher risks according to the preset threshold, so that distribution of prevention and control resources is optimized, timely attention and intervention on the most dangerous area are ensured, accuracy and efficiency of prevention and control of the solenopsis invicta are improved, the system can take measures more pertinently, and harm of the solenopsis invicta is reduced to the greatest extent.
Preferably, step S5 comprises the steps of:
Step S51: carrying out migration path design according to the dangerous migration path prediction data to generate migration path data;
step S52: collecting historical solenopsis invicta diffusion data of the ecological activity range data to generate historical solenopsis invicta diffusion data;
step S53: performing solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data, and generating migration path diffusion data;
step S54: comparing the threshold value of the migration path diffusion data by using a preset safe solenopsis invicta diffusion threshold value, and establishing a path inflection point for migration path data corresponding to the migration path diffusion data when the migration path diffusion data is larger than the preset safe solenopsis invicta diffusion threshold value;
step S55: and carrying out the red fire ant prevention and control track design according to the migration path data and the path inflection points, and generating red fire ant prevention and control track data.
According to the method, migration path design is carried out according to the dangerous migration path prediction data, migration path data are generated, and a safe migration path can be planned based on the recognized dangerous migration path, so that effective implementation of the solenopsis invicta prevention and control work is ensured, and the method is beneficial to reducing propagation of the solenopsis invicta to the greatest extent. The historical solenopsis invicta diffusion data of the ecological activity range are acquired for the ecological activity range data, the historical solenopsis invicta diffusion data are generated, the historical data about the solenopsis invicta diffusion process are provided, the system is helped to know the propagation mode and speed of the solenopsis invicta, and an important reference is provided for subsequent analysis. And carrying out solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data to generate migration path diffusion data, so that the diffusion trend of the solenopsis invicta can be analyzed, the prediction of potential diffusion areas and risks is facilitated, and the better planning of the prevention and control strategy is facilitated. And comparing the threshold value of the migration path diffusion data by using a preset safe solenopsis invicta diffusion threshold value, when the migration path diffusion data is larger than the preset safe solenopsis invicta diffusion threshold value, establishing a path corner for the migration path data corresponding to the migration path diffusion data, and clearly separating a high-risk area from a low-risk area according to the safety threshold value, so that key mark points of a safety path are provided for the system, and the accuracy and the safety of prevention and control tracks are ensured. According to the migration path data and the path inflection points, the red fire ant prevention and control track design is carried out, the red fire ant prevention and control track data is generated, the optimal prevention and control track can be planned according to the diffusion trend and the safety path of the red fire ants, the efficient use of prevention and control resources is ensured, and the successful implementation of prevention and control work is facilitated.
Preferably, step S6 comprises the steps of:
carrying out real-time analysis on the red fire ant diffusion data of the red fire ant prevention and control track data to generate real-time prevention and control track diffusion data;
and carrying out real-time optimization processing on the red fire ant prevention and control track data according to the real-time prevention and control track diffusion data, and carrying out automatic inflection point establishment on the red fire ant prevention and control track data when the real-time prevention and control track diffusion data is monitored to be larger than a preset safe red fire ant diffusion threshold value, so as to generate optimized red fire ant prevention and control track data.
According to the method, the red fire ant diffusion data of the red fire ant prevention and control track is analyzed in real time, the real-time prevention and control track diffusion data is generated, the diffusion condition of the red fire ants is monitored and analyzed in real time, the latest diffusion data is obtained in time, and the method is beneficial to the system to track and deal with the propagation of the red fire ants more accurately. And carrying out real-time optimization processing on the red ant prevention and control track data according to the real-time prevention and control track diffusion data, and when the real-time prevention and control track diffusion data is monitored to be larger than a preset safe red ant diffusion threshold value, carrying out automatic inflection point establishment on the red ant prevention and control track data so as to generate optimized red ant prevention and control track data, automatically adjusting the prevention and control track according to the real-time diffusion condition, ensuring that a system can respond in time at high risk, adjusting the prevention and control strategy, and improving the real-time performance and flexibility of red ant prevention and control.
The present specification provides a track generation system based on control of a solenopsis invicta, for executing the track generation method based on control of a solenopsis invicta as described above, the track generation system based on control of a solenopsis invicta includes:
the solenopsis invicta image acquisition module is used for acquiring forest environment data by utilizing a GIS technology to generate forest environment data; carrying out real-time acquisition on the solenopsis invicta image data of the target analysis area by using electronic monitoring equipment to generate solenopsis invicta image data;
the migration path simulation module establishes migration simulation coordinates by using a GIS technology and the solenopsis invicta image data, and performs migration path simulation mapping processing on the migration simulation coordinates to generate simulated migration path data;
the migration path prediction module is used for carrying out time sequence division processing on the simulated migration path data to generate time sequence migration path data; performing migration path data prediction on the time sequence migration path data by using a long-short memory neural network algorithm to generate migration path prediction data;
the dangerous migration path data acquisition module is used for acquiring an ecological sensitivity report; acquiring ecological activity range data by using a GIS technology to generate ecological activity range data; performing abnormal migration path prediction extraction on migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data; performing migration path risk assessment on abnormal migration path prediction data according to the ecological sensitivity report, and generating migration path risk grade data; extracting dangerous migration path prediction data from abnormal migration path prediction data according to migration path risk level data to obtain dangerous migration path prediction data;
The solenopsis invicta prevention and control track generation module is used for carrying out migration path design according to dangerous migration path prediction data to generate migration path data; collecting historical solenopsis invicta diffusion data of the ecological activity range data to generate historical solenopsis invicta diffusion data; performing solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data, and generating migration path diffusion data; performing red fire ant prevention and control track design according to the migration path data and the migration path diffusion data to generate red fire ant prevention and control track data;
and the red fire ant prevention and control track optimization module is used for carrying out real-time optimization processing on the red fire ant prevention and control track data so as to generate optimized red fire ant prevention and control track data.
The forest environment monitoring system has the beneficial effects that detailed data about forest environments are collected by utilizing the GIS technology, so that the system is helped to know environmental characteristics, data about solenopsis invisibility conditions are obtained, the system can identify potential solenopsis invisibility conditions, the forest environment data are screened by combining the solenopsis invisibility condition data, a target analysis area is generated, the attention range is narrowed, the image data of the solenopsis invisibility are collected in real time through electronic monitoring equipment, the monitoring of the target analysis area is realized, comprehensive environmental data is provided, the distribution area of the solenopsis invisibility is helped to be accurately identified, and basic information and monitoring means are provided for subsequent prevention and control work. The method is characterized in that red fire ant nest node data are successfully acquired based on red fire ant image data, nest position determination is facilitated, migration path data are acquired through the red fire ant image data, a migration route of the red fire ants is revealed, migration simulation coordinates are constructed by means of GIS technology and nest node data, simulation mapping processing is conducted on the migration path data, simulation migration path data are generated, visualization of migration of the red fire ants is facilitated, important data basis is provided for subsequent path analysis and prediction, nest and migration information of the red fire ants are provided, and deeper red fire ant behavior research and prevention and control decision making are supported. The simulation migration path data is divided according to time sequence to generate time sequence migration path data, so that time deduction of the path can be captured more clearly, a long and short memory neural network algorithm is used for building a migration path prediction model, and therefore future migration paths can be predicted. Acquiring an ecological sensitivity report, providing important information about an ecological system for decision making, acquiring ecological activity range data by utilizing a GIS technology, helping to identify an ecological sensitive area, extracting abnormal migration path prediction data based on the ecological activity range data, wherein the paths possibly have adverse effects on the ecological system, carrying out risk assessment on the abnormal migration paths by combining a migration path risk level algorithm and the ecological sensitivity report, and generating migration path risk level data, so that a prevention and control strategy is more targeted, the dangerous migration path prediction data is extracted according to the migration path risk level data so as to concentrate on areas with higher potential risks, and ecological factors are taken into consideration of the red fire ant prevention and control strategy to improve the accuracy, adaptability and ecological friendliness of the strategy, thereby better protecting the ecological environment. According to the dangerous migration path prediction data, migration path design is conducted to generate effective path planning aiming at potential risk areas, historical solenopsis invicta diffusion data are collected, in order to better understand the propagation trend of solenopsis invicta, solenopsis invicta diffusion analysis is conducted by combining the migration path data and the historical diffusion data to generate important information related to the propagation of the solenopsis invicta, the risk areas are determined through comparison with preset safe solenopsis invicta diffusion threshold values, attention of the risk areas is further enhanced, and according to the migration path data and path inflection points, a solenopsis invicta prevention and control track is designed to ensure that proper measures are taken in the risk areas, so that pertinence, efficiency and accuracy of solenopsis invicta prevention and control are improved, and ecological systems and human benefits are better protected. The method has the advantages that the red fire ant prevention and control track data are analyzed in real time to generate the real-time prevention and control track diffusion data, so that the current distribution situation of the red fire ants is helped to be known, when the fact that the real-time prevention and control track diffusion data exceed the preset safe red fire ant diffusion threshold value is monitored, real-time optimization processing of the red fire ant prevention and control track is automatically carried out, and the optimized red fire ant prevention and control track data are generated through means such as automatic inflection point establishment and the like, so that the risk of red fire ant diffusion is timely dealt with, the real-time monitoring and response speed to the red fire ants are helped to be improved, the flexibility and the adaptability of prevention and control strategies are enhanced, and an ecological system is effectively protected and potential hazards are reduced.
Drawings
FIG. 1 is a schematic flow chart of steps of a track generation method based on solenopsis invicta prevention and control;
FIG. 2 is a flowchart illustrating the detailed implementation of step S3 in FIG. 1;
FIG. 3 is a flowchart illustrating the detailed implementation of step S4 in FIG. 1;
the achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
The following is a clear and complete description of the technical method of the present patent in conjunction with the accompanying drawings, and it is evident that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, are intended to fall within the scope of the present invention.
Furthermore, the drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. The functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor methods and/or microcontroller methods.
It will be understood that, although the terms "first," "second," etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
In order to achieve the above objective, referring to fig. 1 to 3, the present invention provides a track generation method based on control of solenopsis invicta, comprising the following steps:
step S1: forest environment data acquisition is carried out by utilizing a GIS technology, and forest environment data is generated; carrying out real-time acquisition on the solenopsis invicta image data of the target analysis area by using electronic monitoring equipment to generate solenopsis invicta image data;
step S2: establishing migration simulation coordinates by using a GIS technology and solenopsis invicta image data, and performing migration path simulation mapping processing on the migration simulation coordinates to generate simulated migration path data;
Step S3: performing time sequence division processing on the simulated migration path data to generate time sequence migration path data; performing migration path data prediction on the time sequence migration path data by using a long-short memory neural network algorithm to generate migration path prediction data;
step S4: acquiring an ecological sensitivity report; acquiring ecological activity range data by using a GIS technology to generate ecological activity range data; performing abnormal migration path prediction extraction on migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data; performing migration path risk assessment on abnormal migration path prediction data according to the ecological sensitivity report, and generating migration path risk grade data; extracting dangerous migration path prediction data from abnormal migration path prediction data according to migration path risk level data to obtain dangerous migration path prediction data;
step S5: carrying out migration path design according to the dangerous migration path prediction data to generate migration path data; collecting historical solenopsis invicta diffusion data of the ecological activity range data to generate historical solenopsis invicta diffusion data; performing solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data, and generating migration path diffusion data; performing red fire ant prevention and control track design according to the migration path data and the migration path diffusion data to generate red fire ant prevention and control track data;
Step S6: and carrying out real-time optimization processing on the red ant prevention and control track data so as to generate optimized red ant prevention and control track data.
According to the invention, forest environment data acquisition is carried out by utilizing a GIS technology, the system can acquire key environment information such as temperature, humidity, topography and the like in real time, the environment of the solenopsis invicta can be accurately understood, the image data of the solenopsis invicta in a target analysis area is acquired in real time by utilizing electronic monitoring equipment, the system acquires instant activity information of the solenopsis invicta, including distribution, quantity, moving paths and the like, and the combination of the data enables the system to accurately grasp the survival condition and behavior of the solenopsis invicta, so that reliable basis is provided for subsequent prevention and control measures, and the prevention and control efficiency and accuracy are improved. The GIS technology is utilized to combine the solenopsis invicta image data to establish migration simulation coordinates, and migration path simulation mapping processing is carried out on the coordinates to generate simulated migration path data, so that migration behaviors of solenopsis invicta can be simulated, movement modes and habits of the solenopsis invicta can be understood in depth, not only can the current position of the solenopsis invicta be tracked, but also possible migration paths of the solenopsis invicta can be predicted, precious information is provided, a solenopsis invicta prevention and control strategy can be formulated more pertinently, and prevention and control accuracy and efficiency are further improved. The simulated migration path data are subjected to time sequence division processing, so that time sequence migration path data are generated, the time sequence migration path data are analyzed and modeled by applying a long and short memory neural network (LSTM) algorithm, migration path prediction data are generated, the actual migration history of solenopsis invicta can be tracked, possible action paths in the future can be predicted, the prevention and control strategy is more intelligent, migration behaviors of the solenopsis invicta can be better dealt with through analysis and prediction of the time sequence data, and the prevention and control efficiency and success rate are improved. By acquiring the ecological sensitivity report, acquiring important information about forest ecological environment, acquiring ecological activity range data by means of GIS technology, forming an ecological activity range data set, extracting abnormal migration paths from migration path prediction data, determining potential risk areas by identifying prediction paths which are inconsistent with the ecological activity range, carrying out risk assessment on the abnormal migration paths according to the ecological sensitivity report, generating risk grade data of the migration paths, analyzing the risk grade data, extracting dangerous migration path prediction data by a system, helping prevention and control personnel to take measures more specifically, protecting the ecological environment from potential threats, improving accuracy and ecological friendliness of red fire ant prevention and control, and integrating ecological factors into prevention and control strategies so that the red fire ant prevention and control strategy is more intelligent and sustainable. According to the dangerous migration path prediction data, the migration path is designed, specific migration path data is generated, prevention and control measures can be planned according to dangerous areas and the red fire ant prediction activity route, pertinence and effectiveness of a prevention and control strategy are improved, historical red fire ant diffusion data acquisition is conducted on ecological activity range data, historical diffusion data are generated, the historical diffusion data are helpful for understanding the behavior mode and trend of past red fire ants, the migration path data and the historical red fire ant diffusion data are analyzed, migration path diffusion data are generated, the propagation mode and speed of the red fire ants can be predicted more accurately, the red fire ant prevention and control track data are generated based on the migration path data and the diffusion data, the prevention and control plan is optimized, the prevention and control track with more pertinence and effectiveness is provided according to migration and diffusion behaviors of the red fire ants, the red fire ants are helped to be controlled more accurately, and influence on ecological environment is reduced. The control track data of the solenopsis invicta is subjected to real-time optimization processing, which means that the system can dynamically adjust the control track according to the latest data and conditions to generate the optimized control track data of the solenopsis invicta, so that the control strategy has higher flexibility and adaptability, and can cope with the changing behavior and new risk area of the solenopsis invicta at any time, thereby improving the real-time performance and efficiency of control, timely adjusting the deployment of control measures through real-time optimization, ensuring that the harm of the solenopsis invicta on ecological environment and agriculture is furthest reduced, and ensuring the success of control work. Therefore, the track generation method based on the prevention and control of the solenopsis invicta not only depends on static ecological data, but also dynamically collects and analyzes relevant data of the solenopsis invicta, and can adapt to the changing situation in time, so that the activity of the solenopsis invicta can be accurately predicted, and the migration mode and the time sequence of the solenopsis invicta are considered, so that the behavior of the solenopsis invicta can be accurately predicted.
In the embodiment of the present invention, as described with reference to fig. 1, the step flow diagram of a track generation method based on control of solenopsis invicta according to the present invention is provided, and in the embodiment, the track generation method based on control of solenopsis invicta includes the following steps:
step S1: forest environment data acquisition is carried out by utilizing a GIS technology, and forest environment data is generated; carrying out real-time acquisition on the solenopsis invicta image data of the target analysis area by using electronic monitoring equipment to generate solenopsis invicta image data;
in the embodiment of the invention, the GIS technology is used for acquiring forest environment data, for example, environmental information about forests including temperature, humidity, soil texture and the like is acquired through a ground sensor, a weather station and a soil detector, so as to generate detailed forest environment data. Then, by means of an electronic monitoring device, such as an infrared camera, the activity of the solenopsis invicta in a target analysis area determined in advance is monitored in real time, and image data of the solenopsis invicta are continuously collected and can be used for subsequent analysis and migration path planning, so that a more effective solenopsis invicta prevention and control strategy is realized.
Step S2: establishing migration simulation coordinates by using a GIS technology and solenopsis invicta image data, and performing migration path simulation mapping processing on the migration simulation coordinates to generate simulated migration path data;
In the embodiment of the invention, the forest environment data and the solenopsis invicta image data acquired before are integrated by a GIS technology, a migration simulation coordinate is established, the coordinate takes the solenopsis invicta nest point node as a central node of the coordinate, the environment data and the solenopsis invicta image data are allowed to be represented in a common coordinate frame, and a consistent space reference is provided for subsequent analysis. Then, in the simulation coordinate system, simulation mapping processing of the migration paths is carried out, possible migration paths of the solenopsis invicta are mapped to the simulation coordinates, various influencing factors of forest environments such as terrains, vegetation, water sources and the like are considered, simulation migration path data are finally generated, accurate simulation and visualization of migration behaviors of the solenopsis invicta are facilitated, and an important basis is provided for next path planning and risk assessment.
Step S3: performing time sequence division processing on the simulated migration path data to generate time sequence migration path data; performing migration path data prediction on the time sequence migration path data by using a long-short memory neural network algorithm to generate migration path prediction data;
in the embodiment of the invention, the time sequence division processing is carried out on the simulation migration path data generated before, the path data are segmented according to the time sequence, the time sequence migration path data are generated, and the time sequence division allows the system to better capture the time evolution characteristics of the migration of the solenopsis invicta, so that the behavior trend of the solenopsis invicta is known more accurately. And processing the time sequence migration path data by using a long short memory neural network (LSTM) algorithm. LSTM is a deep learning model adapted to process sequence data and captures the timing relationships in the data, at which stage LSTM is used to build a predictive model of migration path data that predicts future migration paths of solenopsis invicta based on past migration behavior data, which predictive process generates migration path predictive data concerning future migration behavior of solenopsis invicta.
Step S4: acquiring an ecological sensitivity report; acquiring ecological activity range data by using a GIS technology to generate ecological activity range data; performing abnormal migration path prediction extraction on migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data; performing migration path risk assessment on abnormal migration path prediction data according to the ecological sensitivity report, and generating migration path risk grade data; extracting dangerous migration path prediction data from abnormal migration path prediction data according to migration path risk level data to obtain dangerous migration path prediction data;
in the embodiment of the invention, an ecological sensitivity report is obtained, wherein the report contains key information related to ecological environment protection, such as a protected area, the position of a sensitive ecological system and the like, and the ecological sensitivity report is obtained through historical ecological data acquisition, the severity of damage to ecology caused by the historical solenopsis invicta and expert calculation. And acquiring and generating ecological activity range data by using a GIS technology. This step includes collecting geographical information of the ecosystem to determine which areas are critical for ecological protection, helping the system to pinpoint ecologically sensitive areas, thereby better identifying potential solenopsis invicta intrusion risks. After the ecological activity range data is obtained, the ecological activity range data is used for abnormal migration path prediction, and based on the ecological activity range data, abnormal migration paths related to an ecological sensitive area in the migration path prediction data can be screened out, so that abnormal migration path prediction data are generated. And carrying out migration path risk assessment on abnormal migration path prediction data by using an ecological sensitivity report, wherein the assessment considers the vulnerability of an ecological system and the threat of solenopsis invicta to the ecological environment, and generates migration path risk grade data reflecting the potential threat degree of different migration paths. According to the migration path risk level data, the system further screens out dangerous migration path prediction data, wherein the dangerous migration path prediction data represent migration paths with higher risks, and the dangerous migration paths can form potential threats to the ecological environment and human communities.
Step S5: carrying out migration path design according to the dangerous migration path prediction data to generate migration path data; collecting historical solenopsis invicta diffusion data of the ecological activity range data to generate historical solenopsis invicta diffusion data; performing solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data, and generating migration path diffusion data; performing red fire ant prevention and control track design according to the migration path data and the migration path diffusion data to generate red fire ant prevention and control track data;
in the embodiment of the invention, the migration path is designed by using the dangerous migration path prediction data, the migration path data is generated, the potential dangerous migration path is considered, a relatively safe path is designed, the risk of the propagation of the solenopsis invicta is reduced, and the paths guide the subsequent prevention and control measures. The historical solenopsis invicta diffusion data of the ecological activity range are acquired, and the past diffusion conditions of the solenopsis invicta are recorded according to the data of the ecological activity range, wherein the diffusion conditions comprise information such as distribution, migration paths and the like of the solenopsis invicta, so that the system can better understand the migration mode and the behavior of the solenopsis invicta. According to the migration path data and the historical solenopsis invicta diffusion data, the solenopsis invicta diffusion data of the migration path are analyzed, the analysis process aims at predicting possible diffusion conditions of the solenopsis invicta in the future, and factors such as environment, topography, ecological behaviors of the solenopsis invicta and the like are considered, so that the migration path diffusion data are generated. Based on migration path data and migration path diffusion data, the system performs red fire ant prevention and control track design, and determines the optimal position for placing monitoring and prevention and control facilities in a forest environment so as to prevent the red fire ants from diffusing to the greatest extent, and the prevention and control track data is helpful for formulating a targeted red fire ant prevention and control strategy and protecting an ecological system and agricultural industry from being threatened.
Step S6: and carrying out real-time optimization processing on the red ant prevention and control track data so as to generate optimized red ant prevention and control track data.
In the embodiment of the invention, the red fire ant prevention and control track data is subjected to real-time optimization processing to cope with the condition of continuous change, the existing red fire ant prevention and control track data is monitored and analyzed in real time, and the information about the position and the activity of the red fire ants can be obtained in time by continuously collecting the red fire ant diffusion data. When the real-time control track diffusion data is monitored to be larger than the preset safe solenopsis invicta diffusion threshold value, the system triggers an automatic optimization process, and a path inflection point is established according to the latest data so as to adjust the solenopsis invicta control track and ensure that the solenopsis invicta control track is suitable for the new distribution situation of the solenopsis invicta, so that optimized solenopsis invicta control track data is generated.
Preferably, step S1 comprises the steps of:
step S11: forest environment data acquisition is carried out by utilizing a GIS technology, and forest environment data is generated;
step S12: acquiring solenopsis invicta livability condition data;
step S13: screening a target analysis area of the solenopsis invicta on the basis of the solenopsis invicta livability condition data to generate a target analysis area;
Step S14: and (3) carrying out real-time acquisition on the solenopsis invicta image data of the target analysis area by using the electronic monitoring equipment to generate the solenopsis invicta image data.
The invention utilizes the GIS technology to collect forest environment data, generates forest environment data, provides comprehensive data about forest environment, including information such as topography, vegetation, weather and the like, is beneficial to the system to comprehensively know the ecological environment of the prevention and control area, and provides necessary background information for the follow-up solenopsis invicta prevention and control strategy. And the condition data of the solenopsis invicta suitable for survival can be obtained, and conditions of the solenopsis invicta suitable for survival, such as temperature, humidity, food resources and the like, can be known better, so that the life habit and the behavior mode of the solenopsis invicta can be understood better, and a foundation is provided for subsequent target analysis. The forest environment data is screened based on the solenopsis invicta livability condition data to generate the target analysis area, so that the system is helped to determine the possible area of solenopsis invicta activity, the positioning accuracy is improved, excessive monitoring of the whole area is avoided, and resources are saved. The electronic monitoring equipment is utilized to collect the image data of the solenopsis invicta in the target analysis area in real time to generate the image data of the solenopsis invicta, so that real-time and visual data are provided, a system is allowed to track and monitor the distribution and activity conditions of the solenopsis invicta in time, and the real-time performance and accuracy of prevention and control are improved.
In the embodiment of the invention, the forest environment data acquisition is performed by using a GIS technology (geographic information system), including acquiring information about the geography, topography, weather and the like of the forest, such as tree distribution, topography elevation and the like, so as to generate detailed forest environment data, and provide basic background information for subsequent solenopsis invicta prevention and control. The solenopsis invicta livability data is obtained, and the data can comprise survival, propagation and activity preference of the solenopsis invicta under different environmental conditions, such as temperature, humidity, food supply and the like, and the lienopsis invicta lienopsis is helpful for understanding the behavior and ecological requirements of the solenopsis invicta in different environments. Based on the solenopsis invicta livability condition data, the forest environment data collected before are screened to determine a target analysis area of the solenopsis invicta, and potential solenopsis invicta habitat or propagation areas are identified for subsequent monitoring, prevention and control work. The electronic monitoring equipment is utilized to monitor the target analysis area in real time, and the image data of the solenopsis invicta in the target analysis area are collected, wherein the image data can comprise the distribution, the number and the activity status of the solenopsis invicta, so that a real-time information source is provided for the subsequent data analysis and prevention and control strategies.
Preferably, step S2 comprises the steps of:
step S21: carrying out red fire ant nest node acquisition according to the red fire ant image data to generate red fire ant nest node data;
step S22: carrying out solenopsis invicta migration path acquisition according to the solenopsis invicta image data to generate migration path data;
step S23: and establishing migration simulation coordinates by using a GIS technology and the solenopsis invicta nest node data as central nodes, transmitting migration path data to the migration simulation coordinates for migration path simulation mapping processing, and generating simulation migration path data.
According to the method, the red fire ant nest node acquisition is carried out according to the red fire ant image data, the red fire ant nest node data are generated, nest positions of the red fire ants can be accurately identified and marked, important starting point information is provided for subsequent migration path modeling, and the method is beneficial to more accurately knowing the activity center of the red fire ants. And acquiring the migration paths of the solenopsis invicta according to the image data of the solenopsis invicta, generating migration path data, and acquiring migration behavior data of the solenopsis invicta by monitoring and recording the actual migration paths of the solenopsis invicta, so that migration habits and modes of the solenopsis invicta are more accurately simulated and analyzed. The GIS technology and the solenopsis invicta nest node data are used as central nodes to establish migration simulation coordinates, migration path data are transmitted to the migration simulation coordinates to carry out migration path simulation mapping processing, simulation migration path data are generated, the actual nest nodes are combined with the simulation coordinates to create a virtual environment capable of simulating the migration of the solenopsis invicta, so that a system can simulate and analyze the migration behavior of the solenopsis invicta, and understanding and predicting capacity of a migration mode of the solenopsis invicta are further improved.
In the embodiment of the invention, the red fire ant nest node is acquired according to the red fire ant image data, the position of the red fire ant nest is identified and positioned from the image, the red fire ant nest node data is generated, for example, by an image processing technology, the system can detect the visual characteristics of the red fire ant nest, such as the color and the shape, and mark the visual characteristics as the node. According to the same solenopsis invicta image data, the acquisition of the solenopsis invicta migration paths is carried out, the moving paths of the solenopsis invicta in different time periods can be tracked and recorded, and migration path data is generated and used for knowing the migration modes and trends of the solenopsis invicta. And using a GIS technology and the previously acquired red fire nest node data, taking the nodes as central nodes, establishing a migration simulation coordinate system, transmitting the previously acquired migration path data to the migration simulation coordinate system, performing simulation mapping processing on the migration paths, mapping the actual migration paths into a simulation environment, and generating simulation migration path data for subsequent analysis and simulation.
Preferably, step S3 comprises the steps of:
step S31: performing time sequence division processing on the simulated migration path data to generate time sequence migration path data;
Step S32: establishing a mapping relation of migration path prediction by using a long-short memory neural network algorithm, and generating an initial migration path prediction model;
step S33: carrying out data division processing on the time-series migration path data to respectively generate a time-series migration path training set and a time-series migration path testing set;
step S34: performing model training on the initial migration path prediction model by using a time sequence migration path training set to generate a migration path prediction model;
step S35: and transmitting the time sequence migration path test set to a migration path prediction model to predict migration path data, and generating migration path prediction data.
According to the method, the simulated migration path data are subjected to time sequence division processing, the time sequence migration path data are generated, and the migration path data are divided according to time sequence, so that the system is facilitated to capture the time sequence characteristics of the solenopsis invicta migration, and the time sequence and the accuracy of the migration model are improved. The mapping relation of migration path prediction is established by using a long-short memory neural network algorithm, an initial migration path prediction model is generated, and a deep learning algorithm is introduced, so that the system can better capture a complex mode in time sequence data, and a basic migration path prediction model is established. And carrying out data division processing on the time-series migration path data to respectively generate a time-series migration path training set and a time-series migration path testing set, ensuring that enough data are used for model training and verification, and being beneficial to improving the generalization performance and reliability of a migration path prediction model. Model training is carried out on the initial migration path prediction model by using the time sequence migration path training set, so that a migration path prediction model is generated, and the system can learn the complex relation of time sequence migration data through the training model, so that the accuracy and usability of the prediction model are further improved. The time sequence migration path test set is transmitted to the migration path prediction model to predict migration path data, migration path prediction data are generated, new time sequence migration data can be accurately predicted by using the trained model, valuable prediction information is provided for the migration path of the solenopsis invicta, and the prevention and control strategy can be formulated more accurately.
In the embodiment of the invention, the generated simulated migration path data is subjected to time sequence division processing, the migration path data is divided and organized according to time sequence, and the time sequence migration path data is generated, for example, the migration path in a period of time can be divided into different time periods according to time sequence, so that the subsequent time sequence analysis can be performed. A mapping relation of migration path prediction is established by utilizing a long and short memory neural network (LSTM) algorithm, an initial migration path prediction model is generated, the LSTM is a deep learning algorithm suitable for sequence data, the LSTM can be used for capturing a mode and trend of time sequence data, and the LSTM model is trained to enable the LSTM model to understand relevance and regularity of the time sequence migration path data, so that a foundation is provided for subsequent prediction. And carrying out data division processing on the time-series migration path data to respectively generate a time-series migration path training set and a time-series migration path testing set, and ensuring the independence and the reliability of the data when training and testing a migration path prediction model. Model training is carried out on an initial migration path prediction model by using a time sequence migration path training set, and the model learns how to infer a future migration path from known time sequence migration path data through training, so that a migration path prediction model is generated. The time sequence migration path test set is transmitted to a trained migration path prediction model to conduct migration path data prediction, the model uses test data to verify prediction performance of the model, migration path prediction data are generated, the data can be used for predicting migration paths of solenopsis invicta, important information support is provided for a subsequent prevention and control strategy, and a system is helped to better understand migration behaviors of the solenopsis invicta and conduct corresponding prediction.
Preferably, step S4 comprises the steps of:
step S41: acquiring an ecological sensitivity report;
step S42: acquiring ecological activity range data by using a GIS technology to generate ecological activity range data;
step S43: performing abnormal migration path prediction extraction on migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data;
step S44: performing migration path risk assessment calculation on abnormal migration path prediction data by using a migration path risk level algorithm and an ecological sensitivity report to generate migration path risk level data;
step S45: and extracting dangerous migration path prediction data from the abnormal migration path prediction data according to the migration path risk level data so as to obtain dangerous migration path prediction data.
The invention acquires the ecological sensitivity report, can acquire the detailed report about the ecological system of the prevention and control area, comprises the information of vulnerability of the ecological environment, biological diversity, vegetation coverage and the like, and the ecological sensitivity report provides the assessment of the vulnerability of the ecological environment, thereby being beneficial to better understanding the ecological risk and potential influence of the system. The GIS technology is utilized to collect ecological activity range data, and ecological activity range data are generated, so that accurate data related to different ecological systems such as wetlands, forests, farmlands and the like can be obtained, and the system is facilitated to better identify potential ecological sensitive areas and survival conditions of solenopsis invicta. And carrying out abnormal migration path prediction extraction on the migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data, so that a prediction path which is inconsistent with the ecological activity range can be identified, a prevention and control key area is further screened and focused, and redundant monitoring and resource waste are reduced. And carrying out migration path risk assessment calculation on abnormal migration path prediction data by using a migration path risk level algorithm and an ecological sensitivity report to generate migration path risk level data, comprehensively considering the relevance of ecological risk factors and solenopsis invicta migration paths, generating ecological sensitivity-based risk level data, and being beneficial to more pertinently formulating a prevention and control strategy. And extracting dangerous migration path prediction data from the abnormal migration path prediction data according to the migration path risk level data to obtain dangerous migration path prediction data, and identifying the migration path with the highest risk, so that the distribution of prevention and control resources is optimized, the priority attention of a high-risk area is ensured, and the accuracy and the urgency of prevention and control of the solenopsis invicta are improved.
As an example of the present invention, referring to fig. 2, a detailed implementation step flow diagram of step S4 in fig. 1 is shown, where step S4 includes:
step S41: acquiring an ecological sensitivity report;
in the embodiment of the invention, an ecological sensitivity report is obtained, wherein the report possibly contains various information about a forest ecological system, such as vegetation distribution, meteorological data, soil characteristics and the like, which are important for understanding the ecological sensitivity of the environment, the ecological sensitivity report is obtained through historical ecological data acquisition, the severity of damage to ecology caused by the solenopsis invicta and expert calculation.
Step S42: acquiring ecological activity range data by using a GIS technology to generate ecological activity range data;
in the embodiment of the invention, the GIS technology is utilized to collect the ecological activity range data, so that the ecological activity range data is generated, and the data can comprise information such as habitats, migration paths, food sources and the like of different biological species, thereby being beneficial to determining which areas are most beneficial to survival and diffusion of the solenopsis invicta.
Step S43: performing abnormal migration path prediction extraction on migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data;
In the embodiment of the invention, the extraction of the abnormal migration path prediction is performed on the previously generated migration path prediction data based on the ecological activity range data, and the abnormal migration paths falling in the areas different from the normal ecological activity range are identified, because the paths possibly indicate potential risks.
Step S44: performing migration path risk assessment calculation on abnormal migration path prediction data by using a migration path risk level algorithm and an ecological sensitivity report to generate migration path risk level data;
in the embodiment of the invention, specific migration path risk level algorithm and ecological sensitivity report are used for carrying out calculation of migration path risk assessment on abnormal migration path prediction data, the assessment calculation can determine potential threat levels of abnormal paths, and judge which paths have the most serious influence on an ecological system according to the information of the ecological sensitivity report, or can carry out migration path risk assessment calculation on the abnormal migration path prediction data through a conventional risk level calculation formula, and can also evaluate the risk level of the abnormal migration path prediction data, so as to generate migration path risk level data.
Step S45: and extracting dangerous migration path prediction data from the abnormal migration path prediction data according to the migration path risk level data so as to obtain dangerous migration path prediction data.
In the embodiment of the invention, the dangerous migration path prediction data is extracted from the abnormal migration path prediction data according to the migration path risk level data, and those migration paths with high risk and potential threat are identified, so that subsequent prevention and control measures can be formulated and implemented in a targeted manner, and the dangerous migration paths of the potential solenopsis invicta threatening the ecological environment are evaluated and identified under the condition of considering ecological factors.
Preferably, the migration path risk level algorithm in step S44 is as follows:
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in the method, in the process of the invention,expressed as migration path risk level data, < +.>Expressed as the number of risk factors>Denoted as +.>Risk factors,/->Migration path length expressed as abnormal migration path prediction data,/for each of the plurality of blocks>Temperature influence coefficient expressed as physiological sensitivity report, < ->Temperature data expressed as abnormal migration path prediction data,/and/or>Humidity influence coefficient expressed as physiological sensitivity report, < ->Humidity data expressed as abnormal migration path prediction data,/and/or>Expressed as the number of external risk factors, +.>Denoted as +.>Individual external risk factors,/->Expressed as extra migration path length generated from external risk influencing factors,/for >An anomaly adjustment value expressed as migration path risk level data.
The invention utilizes a migration path risk level calculationThe method fully considers the number of risk factorsFirst->Personal risk factor->Migration path length of abnormal migration path prediction data +.>Temperature influence coefficient reported by ecological sensitivity +.>Temperature data of abnormal migration path prediction data +.>Humidity influence coefficient of ecological sensitivity report +.>Humidity data of abnormal migration path prediction data +.>Number of external risk factors->First->Personal external risk influence coefficient->Additional migration path length generated according to external risk influencing factors>And interactions between functions to form a functional relationship:
that is to say,the functional relation can be used for evaluating the risk level of the abnormal migration path prediction data, so that the functional relation is used for carrying out a corresponding prevention and control strategy on the abnormal migration path prediction data with high risk level in the subsequent step. The number of risk factors is used to evaluate the number of internal factors of the risk. These internal factors may include factors related to solenopsis invicta ecology, such as temperature, humidity, food resources, etc., reflecting the complexity and diversity of the internal factors considered by the algorithm; first- >The risk influence coefficients reflect that each risk factor has a related weight or influence coefficient, the influence degree of each factor on the total risk is measured, and the influence of the temperature on the activity of the solenopsis invicta is possibly more important than the humidity, so that the corresponding parameter value is higher; abnormal migration path length, typically expressed in certain distance units, longer paths may increase risk; the temperature influence coefficient of the ecological sensitivity report and the humidity influence coefficient of the ecological sensitivity report respectively represent the influence weights of the temperature and humidity factors in the ecological sensitivity report, so that the algorithm is helped to more accurately consider the influence of different meteorological conditions on the migration path; the temperature data of the abnormal migration path prediction data and the humidity data of the abnormal migration path prediction data are related to the abnormal migration path, and respectively represent the values of the temperature and the humidity, and can be actual measured values obtained from a sensor or meteorological data; the number of external risk influencing factors is used for evaluating the number of factors influenced by external factors, and the external factors may include weather conditions, human activities and the like; first->Each external risk factor has an associated weight or influence coefficient that measures the extent to which each factor affects the overall risk; additional migration path lengths generated based on external risk influencing factors, such as increased migration path lengths due to bad weather. The functional relationship fully considers a plurality of risk factors, including internal and external factors The factors are comprehensively considered, so that a more comprehensive assessment of migration path risks is provided, and potential risks of solenopsis invicta diffusion are reflected more accurately. Abnormality adjustment value +.>And the functional relation is adjusted and corrected, so that the error influence caused by abnormal data or error items is reduced, the migration path risk grade data is generated more accurately, and the accuracy and reliability of migration path risk assessment calculation on abnormal migration path prediction data are improved. Meanwhile, the adjustment value in the formula can be adjusted according to actual conditions and is applied to different abnormal migration path prediction data, so that the flexibility and applicability of the algorithm are improved. />
Preferably, step S45 comprises the steps of:
and performing data screening on the migration path risk level data according to a preset migration path risk level threshold, and performing data extraction on abnormal migration path prediction data corresponding to the migration path risk level data when the migration path risk level data is larger than the preset migration path risk level threshold so as to obtain dangerous migration path prediction data.
According to the method, data screening is carried out on migration path risk level data according to the preset migration path risk level threshold, when the migration path risk level data is larger than the preset migration path risk level threshold, data extraction is carried out on abnormal migration path prediction data corresponding to the migration path risk level data so as to obtain dangerous migration path prediction data, and the system can automatically screen out migration paths with higher risks according to the preset threshold, so that distribution of prevention and control resources is optimized, timely attention and intervention on the most dangerous area are ensured, accuracy and efficiency of prevention and control of the solenopsis invicta are improved, the system can take measures more pertinently, and harm of the solenopsis invicta is reduced to the greatest extent.
In the embodiment of the invention, data screening is performed according to the preset migration path risk level threshold, for example, a migration path risk level threshold is set, for example, a specific value is set, and those migration paths marked as high risk are screened. When the risk level data of the migration paths is greater than a preset risk level threshold value of the migration paths, data extraction is performed on the paths with high risk, for example, when data are analyzed, if the risk level of a specific path is greater than the risk level threshold value, abnormal migration path prediction data related to the path are extracted and marked as dangerous migration path prediction data, the data may include information about the number of red fire ants, migration speed, possibly invaded areas and the like, and when the risk level data of the migration paths is not greater than the preset risk level threshold value of the migration paths, no processing is performed. And setting an automatic warning standard according to the risk level so as to identify the most dangerous migration path, and taking necessary measures in a targeted manner so as to minimize the potential threat of the solenopsis invicta. This helps to improve the efficiency and accuracy of the fire ant control work, ensuring optimal use of resources.
Preferably, step S5 comprises the steps of:
step S51: carrying out migration path design according to the dangerous migration path prediction data to generate migration path data;
step S52: collecting historical solenopsis invicta diffusion data of the ecological activity range data to generate historical solenopsis invicta diffusion data;
step S53: performing solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data, and generating migration path diffusion data;
step S54: comparing the threshold value of the migration path diffusion data by using a preset safe solenopsis invicta diffusion threshold value, and establishing a path inflection point for migration path data corresponding to the migration path diffusion data when the migration path diffusion data is larger than the preset safe solenopsis invicta diffusion threshold value;
step S55: and carrying out the red fire ant prevention and control track design according to the migration path data and the path inflection points, and generating red fire ant prevention and control track data.
According to the method, migration path design is carried out according to the dangerous migration path prediction data, migration path data are generated, and a safe migration path can be planned based on the recognized dangerous migration path, so that effective implementation of the solenopsis invicta prevention and control work is ensured, and the method is beneficial to reducing propagation of the solenopsis invicta to the greatest extent. The historical solenopsis invicta diffusion data of the ecological activity range are acquired for the ecological activity range data, the historical solenopsis invicta diffusion data are generated, the historical data about the solenopsis invicta diffusion process are provided, the system is helped to know the propagation mode and speed of the solenopsis invicta, and an important reference is provided for subsequent analysis. And carrying out solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data to generate migration path diffusion data, so that the diffusion trend of the solenopsis invicta can be analyzed, the prediction of potential diffusion areas and risks is facilitated, and the better planning of the prevention and control strategy is facilitated. And comparing the threshold value of the migration path diffusion data by using a preset safe solenopsis invicta diffusion threshold value, when the migration path diffusion data is larger than the preset safe solenopsis invicta diffusion threshold value, establishing a path corner for the migration path data corresponding to the migration path diffusion data, and clearly separating a high-risk area from a low-risk area according to the safety threshold value, so that key mark points of a safety path are provided for the system, and the accuracy and the safety of prevention and control tracks are ensured. According to the migration path data and the path inflection points, the red fire ant prevention and control track design is carried out, the red fire ant prevention and control track data is generated, the optimal prevention and control track can be planned according to the diffusion trend and the safety path of the red fire ants, the efficient use of prevention and control resources is ensured, and the successful implementation of prevention and control work is facilitated.
As an example of the present invention, referring to fig. 3, a detailed implementation step flow diagram of step S5 in fig. 1 is shown, where step S5 includes:
step S51: carrying out migration path design according to the dangerous migration path prediction data to generate migration path data;
in the embodiment of the invention, the migration path is designed according to the dangerous migration path prediction data, and the prediction data is assumed to indicate the high-risk solenopsis invicta migration path in a certain area, and a proper migration path is prepared according to the information, which may include road blocking adjustment, monitoring point setting or other control measures, so that the generated migration path data becomes the basis of subsequent solenopsis invicta prevention and control work.
Step S52: collecting historical solenopsis invicta diffusion data of the ecological activity range data to generate historical solenopsis invicta diffusion data;
in the embodiment of the invention, the ecological activity range data is collected by the historical solenopsis invicta diffusion data of the ecological activity range, and the ecological activity range data is monitored to obtain the detailed information about the past diffusion behavior of the solenopsis invicta, for example, the propagation mode of the solenopsis invicta can be better known by collecting the historical data such as migration track, diffusion speed and range of the solenopsis invicta.
Step S53: performing solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data, and generating migration path diffusion data;
in the embodiment of the invention, migration path data are collected, wherein the data comprise migration track, density, speed and other information of the solenopsis invicta, and historical solenopsis invicta diffusion data are obtained, and the data comprise distribution, diffusion mode, seasonal change and other information of the solenopsis invicta in a past period of time. The diffusion mode of the solenopsis invicta is studied by using a data analysis technology, such as space statistical analysis, time series analysis and the like, whether abnormal diffusion behaviors, such as large-scale migration or rapid propagation of the solenopsis invicta exist or not can be identified by comparing the migration path data with the historical diffusion data, and migration path diffusion data are generated based on the result of the data analysis, and the data describe the diffusion condition of the solenopsis invicta in the current environment and comprise information of diffusion speed, direction, diffusion range and the like.
Step S54: comparing the threshold value of the migration path diffusion data by using a preset safe solenopsis invicta diffusion threshold value, and establishing a path inflection point for migration path data corresponding to the migration path diffusion data when the migration path diffusion data is larger than the preset safe solenopsis invicta diffusion threshold value;
In the embodiment of the invention, the preset safe solenopsis invicta diffusion threshold value is used for comparing the threshold value of the migration path diffusion data. If the value of the migration path diffusion data exceeds this threshold, these data points will be marked, indicating a potentially high risk in these areas.
Step S55: and carrying out the red fire ant prevention and control track design according to the migration path data and the path inflection points, and generating red fire ant prevention and control track data.
In the embodiment of the invention, the design of the red fire ant prevention and control track is carried out according to the migration path data and the marked path inflection points, the marked high-risk areas are considered, and corresponding prevention and control strategies are formulated so as to ensure that proper actions are taken in the migration process of the red fire ants, reduce the propagation of the red fire ants to the greatest extent, and the method comprises the steps of increasing the monitoring frequency, adjusting the position of the monitoring equipment or changing the prevention and control measures, thereby being beneficial to improving the efficiency and the accuracy of the red fire ant prevention and control work so as to better protect the ecological environment and the agricultural industry.
Preferably, step S6 comprises the steps of:
carrying out real-time analysis on the red fire ant diffusion data of the red fire ant prevention and control track data to generate real-time prevention and control track diffusion data;
And carrying out real-time optimization processing on the red fire ant prevention and control track data according to the real-time prevention and control track diffusion data, and carrying out automatic inflection point establishment on the red fire ant prevention and control track data when the real-time prevention and control track diffusion data is monitored to be larger than a preset safe red fire ant diffusion threshold value, so as to generate optimized red fire ant prevention and control track data.
According to the method, the red fire ant diffusion data of the red fire ant prevention and control track is analyzed in real time, the real-time prevention and control track diffusion data is generated, the diffusion condition of the red fire ants is monitored and analyzed in real time, the latest diffusion data is obtained in time, and the method is beneficial to the system to track and deal with the propagation of the red fire ants more accurately. And carrying out real-time optimization processing on the red ant prevention and control track data according to the real-time prevention and control track diffusion data, and when the real-time prevention and control track diffusion data is monitored to be larger than a preset safe red ant diffusion threshold value, carrying out automatic inflection point establishment on the red ant prevention and control track data so as to generate optimized red ant prevention and control track data, automatically adjusting the prevention and control track according to the real-time diffusion condition, ensuring that a system can respond in time at high risk, adjusting the prevention and control strategy, and improving the real-time performance and flexibility of red ant prevention and control.
In the embodiment of the invention, the red fire ant diffusion data of the red fire ant prevention and control track data are analyzed in real time, the actual migration condition of the red fire ants is continuously monitored, and the diffusion condition of the migration path is continuously updated according to the collected data, for example, the position and the movement mode of the red fire ants can be obtained in real time by using a sensor, monitoring equipment or satellite images. And carrying out real-time optimization processing on the red fire ant prevention and control track data based on the real-time prevention and control track diffusion data, automatically adjusting the red fire ant prevention and control track according to the latest data so as to cope with the dynamic diffusion condition of the red fire ants, triggering an automatic inflection point to establish when the real-time prevention and control track diffusion data are monitored to be larger than a preset safe red fire ant diffusion threshold value, indicating that the diffusion of the red fire ants exceeds a safe range, and not carrying out corresponding operation when the real-time prevention and control track diffusion data are monitored to be not larger than the preset safe red fire ant diffusion threshold value, so that the original prevention and control track migration path is maintained.
The present specification provides a track generation system based on control of a solenopsis invicta, for executing the track generation method based on control of a solenopsis invicta as described above, the track generation system based on control of a solenopsis invicta includes:
The solenopsis invicta image acquisition module is used for acquiring forest environment data by utilizing a GIS technology to generate forest environment data; carrying out real-time acquisition on the solenopsis invicta image data of the target analysis area by using electronic monitoring equipment to generate solenopsis invicta image data;
the migration path simulation module establishes migration simulation coordinates by using a GIS technology and the solenopsis invicta image data, and performs migration path simulation mapping processing on the migration simulation coordinates to generate simulated migration path data;
the migration path prediction module is used for carrying out time sequence division processing on the simulated migration path data to generate time sequence migration path data; performing migration path data prediction on the time sequence migration path data by using a long-short memory neural network algorithm to generate migration path prediction data;
the dangerous migration path data acquisition module is used for acquiring an ecological sensitivity report; acquiring ecological activity range data by using a GIS technology to generate ecological activity range data; performing abnormal migration path prediction extraction on migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data; performing migration path risk assessment on abnormal migration path prediction data according to the ecological sensitivity report, and generating migration path risk grade data; extracting dangerous migration path prediction data from abnormal migration path prediction data according to migration path risk level data to obtain dangerous migration path prediction data;
The solenopsis invicta prevention and control track generation module is used for carrying out migration path design according to dangerous migration path prediction data to generate migration path data; collecting historical solenopsis invicta diffusion data of the ecological activity range data to generate historical solenopsis invicta diffusion data; performing solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data, and generating migration path diffusion data; performing red fire ant prevention and control track design according to the migration path data and the migration path diffusion data to generate red fire ant prevention and control track data;
and the red fire ant prevention and control track optimization module is used for carrying out real-time optimization processing on the red fire ant prevention and control track data so as to generate optimized red fire ant prevention and control track data.
The forest environment monitoring system has the beneficial effects that detailed data about forest environments are collected by utilizing the GIS technology, so that the system is helped to know environmental characteristics, data about solenopsis invisibility conditions are obtained, the system can identify potential solenopsis invisibility conditions, the forest environment data are screened by combining the solenopsis invisibility condition data, a target analysis area is generated, the attention range is narrowed, the image data of the solenopsis invisibility are collected in real time through electronic monitoring equipment, the monitoring of the target analysis area is realized, comprehensive environmental data is provided, the distribution area of the solenopsis invisibility is helped to be accurately identified, and basic information and monitoring means are provided for subsequent prevention and control work. The method is characterized in that red fire ant nest node data are successfully acquired based on red fire ant image data, nest position determination is facilitated, migration path data are acquired through the red fire ant image data, a migration route of the red fire ants is revealed, migration simulation coordinates are constructed by means of GIS technology and nest node data, simulation mapping processing is conducted on the migration path data, simulation migration path data are generated, visualization of migration of the red fire ants is facilitated, important data basis is provided for subsequent path analysis and prediction, nest and migration information of the red fire ants are provided, and deeper red fire ant behavior research and prevention and control decision making are supported. The simulation migration path data is divided according to time sequence to generate time sequence migration path data, so that time deduction of the path can be captured more clearly, a long and short memory neural network algorithm is used for building a migration path prediction model, and therefore future migration paths can be predicted. Acquiring an ecological sensitivity report, providing important information about an ecological system for decision making, acquiring ecological activity range data by utilizing a GIS technology, helping to identify an ecological sensitive area, extracting abnormal migration path prediction data based on the ecological activity range data, wherein the paths possibly have adverse effects on the ecological system, carrying out risk assessment on the abnormal migration paths by combining a migration path risk level algorithm and the ecological sensitivity report, and generating migration path risk level data, so that a prevention and control strategy is more targeted, the dangerous migration path prediction data is extracted according to the migration path risk level data so as to concentrate on areas with higher potential risks, and ecological factors are taken into consideration of the red fire ant prevention and control strategy to improve the accuracy, adaptability and ecological friendliness of the strategy, thereby better protecting the ecological environment. According to the dangerous migration path prediction data, migration path design is conducted to generate effective path planning aiming at potential risk areas, historical solenopsis invicta diffusion data are collected, in order to better understand the propagation trend of solenopsis invicta, solenopsis invicta diffusion analysis is conducted by combining the migration path data and the historical diffusion data to generate important information related to the propagation of the solenopsis invicta, the risk areas are determined through comparison with preset safe solenopsis invicta diffusion threshold values, attention of the risk areas is further enhanced, and according to the migration path data and path inflection points, a solenopsis invicta prevention and control track is designed to ensure that proper measures are taken in the risk areas, so that pertinence, efficiency and accuracy of solenopsis invicta prevention and control are improved, and ecological systems and human benefits are better protected. The method has the advantages that the red fire ant prevention and control track data are analyzed in real time to generate the real-time prevention and control track diffusion data, so that the current distribution situation of the red fire ants is helped to be known, when the fact that the real-time prevention and control track diffusion data exceed the preset safe red fire ant diffusion threshold value is monitored, real-time optimization processing of the red fire ant prevention and control track is automatically carried out, and the optimized red fire ant prevention and control track data are generated through means such as automatic inflection point establishment and the like, so that the risk of red fire ant diffusion is timely dealt with, the real-time monitoring and response speed to the red fire ants are helped to be improved, the flexibility and the adaptability of prevention and control strategies are enhanced, and an ecological system is effectively protected and potential hazards are reduced.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. The track generation method based on the control of the solenopsis invicta is characterized by comprising the following steps of:
step S1: forest environment data acquisition is carried out by utilizing a GIS technology, and forest environment data is generated; carrying out real-time acquisition on the solenopsis invicta image data of the target analysis area by using electronic monitoring equipment to generate solenopsis invicta image data;
Step S2: establishing migration simulation coordinates by using a GIS technology and solenopsis invicta image data, and performing migration path simulation mapping processing on the migration simulation coordinates to generate simulated migration path data;
step S3: performing time sequence division processing on the simulated migration path data to generate time sequence migration path data; performing migration path data prediction on the time sequence migration path data by using a long-short memory neural network algorithm to generate migration path prediction data;
step S4: acquiring an ecological sensitivity report; acquiring ecological activity range data by using a GIS technology to generate ecological activity range data; performing abnormal migration path prediction extraction on migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data; performing migration path risk assessment on abnormal migration path prediction data according to the ecological sensitivity report, and generating migration path risk grade data; extracting dangerous migration path prediction data from abnormal migration path prediction data according to migration path risk level data to obtain dangerous migration path prediction data;
step S5: carrying out migration path design according to the dangerous migration path prediction data to generate migration path data; collecting historical solenopsis invicta diffusion data of the ecological activity range data to generate historical solenopsis invicta diffusion data; performing solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data, and generating migration path diffusion data; performing red fire ant prevention and control track design according to the migration path data and the migration path diffusion data to generate red fire ant prevention and control track data;
Step S6: and carrying out real-time optimization processing on the red ant prevention and control track data so as to generate optimized red ant prevention and control track data.
2. The track generation method based on the control of solenopsis invicta as claimed in claim 1, wherein step S1 comprises the steps of:
step S11: forest environment data acquisition is carried out by utilizing a GIS technology, and forest environment data is generated;
step S12: acquiring solenopsis invicta livability condition data;
step S13: screening a target analysis area of the solenopsis invicta on the basis of the solenopsis invicta livability condition data to generate a target analysis area;
step S14: and (3) carrying out real-time acquisition on the solenopsis invicta image data of the target analysis area by using the electronic monitoring equipment to generate the solenopsis invicta image data.
3. The track generation method based on the control of solenopsis invicta as claimed in claim 2, wherein step S2 comprises the steps of:
step S21: carrying out red fire ant nest node acquisition according to the red fire ant image data to generate red fire ant nest node data;
step S22: carrying out solenopsis invicta migration path acquisition according to the solenopsis invicta image data to generate migration path data;
Step S23: and establishing migration simulation coordinates by using a GIS technology and the solenopsis invicta nest node data as central nodes, transmitting migration path data to the migration simulation coordinates for migration path simulation mapping processing, and generating simulation migration path data.
4. The track generation method based on the control of solenopsis invicta as claimed in claim 3, wherein the step S3 comprises the steps of:
step S31: performing time sequence division processing on the simulated migration path data to generate time sequence migration path data;
step S32: establishing a mapping relation of migration path prediction by using a long-short memory neural network algorithm, and generating an initial migration path prediction model;
step S33: carrying out data division processing on the time-series migration path data to respectively generate a time-series migration path training set and a time-series migration path testing set;
step S34: performing model training on the initial migration path prediction model by using a time sequence migration path training set to generate a migration path prediction model;
step S35: and transmitting the time sequence migration path test set to a migration path prediction model to predict migration path data, and generating migration path prediction data.
5. The method for generating a track based on the control of solenopsis invicta as claimed in claim 4, wherein step S4 comprises the steps of:
Step S41: acquiring an ecological sensitivity report;
step S42: acquiring ecological activity range data by using a GIS technology to generate ecological activity range data;
step S43: performing abnormal migration path prediction extraction on migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data;
step S44: performing migration path risk assessment calculation on abnormal migration path prediction data by using a migration path risk level algorithm and an ecological sensitivity report to generate migration path risk level data;
step S45: and extracting dangerous migration path prediction data from the abnormal migration path prediction data according to the migration path risk level data so as to obtain dangerous migration path prediction data.
6. The method for generating a track based on the control of solenopsis invicta as set forth in claim 5, wherein the migration path risk level algorithm in step S44 is as follows:
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in the method, in the process of the invention,expressed as migration path risk level data, < +.>Expressed as the number of risk factors>Denoted as +.>Risk factors,/->Migration path length expressed as abnormal migration path prediction data,/for each of the plurality of blocks>Temperature influence coefficient expressed as physiological sensitivity report, < - >Temperature data expressed as abnormal migration path prediction data,/and/or>Humidity influence coefficient expressed as physiological sensitivity report, < ->Humidity data expressed as abnormal migration path prediction data,/and/or>Expressed as external risk influenceQuantity of factors (I)>Denoted as +.>Individual external risk factors,/->Expressed as extra migration path length generated from external risk influencing factors,/for>An anomaly adjustment value expressed as migration path risk level data.
7. The method for generating a track based on the control of solenopsis invicta as claimed in claim 6, wherein step S45 comprises the steps of:
and performing data screening on the migration path risk level data according to a preset migration path risk level threshold, and performing data extraction on abnormal migration path prediction data corresponding to the migration path risk level data when the migration path risk level data is larger than the preset migration path risk level threshold so as to obtain dangerous migration path prediction data.
8. The method for generating a track based on the control of solenopsis invicta as claimed in claim 7, wherein the step S5 comprises the steps of:
step S51: carrying out migration path design according to the dangerous migration path prediction data to generate migration path data;
Step S52: collecting historical solenopsis invicta diffusion data of the ecological activity range data to generate historical solenopsis invicta diffusion data;
step S53: performing solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data, and generating migration path diffusion data;
step S54: comparing the threshold value of the migration path diffusion data by using a preset safe solenopsis invicta diffusion threshold value, and establishing a path inflection point for migration path data corresponding to the migration path diffusion data when the migration path diffusion data is larger than the preset safe solenopsis invicta diffusion threshold value;
step S55: and carrying out the red fire ant prevention and control track design according to the migration path data and the path inflection points, and generating red fire ant prevention and control track data.
9. The method for generating a track based on the control of solenopsis invicta as claimed in claim 8, wherein step S6 comprises the steps of:
carrying out real-time analysis on the red fire ant diffusion data of the red fire ant prevention and control track data to generate real-time prevention and control track diffusion data;
and carrying out real-time optimization processing on the red fire ant prevention and control track data according to the real-time prevention and control track diffusion data, and carrying out automatic inflection point establishment on the red fire ant prevention and control track data when the real-time prevention and control track diffusion data is monitored to be larger than a preset safe red fire ant diffusion threshold value, so as to generate optimized red fire ant prevention and control track data.
10. A track generation system based on control of a solenopsis invicta, characterized by being used for executing the track generation method based on control of a solenopsis invicta as set forth in claim 1, comprising:
the solenopsis invicta image acquisition module is used for acquiring forest environment data by utilizing a GIS technology to generate forest environment data; carrying out real-time acquisition on the solenopsis invicta image data of the target analysis area by using electronic monitoring equipment to generate solenopsis invicta image data;
the migration path simulation module establishes migration simulation coordinates by using a GIS technology and the solenopsis invicta image data, and performs migration path simulation mapping processing on the migration simulation coordinates to generate simulated migration path data;
the migration path prediction module is used for carrying out time sequence division processing on the simulated migration path data to generate time sequence migration path data; performing migration path data prediction on the time sequence migration path data by using a long-short memory neural network algorithm to generate migration path prediction data;
the dangerous migration path data acquisition module is used for acquiring an ecological sensitivity report; acquiring ecological activity range data by using a GIS technology to generate ecological activity range data; performing abnormal migration path prediction extraction on migration path prediction data based on the ecological activity range data to generate abnormal migration path prediction data; performing migration path risk assessment on abnormal migration path prediction data according to the ecological sensitivity report, and generating migration path risk grade data; extracting dangerous migration path prediction data from abnormal migration path prediction data according to migration path risk level data to obtain dangerous migration path prediction data;
The solenopsis invicta prevention and control track generation module is used for carrying out migration path design according to dangerous migration path prediction data to generate migration path data; collecting historical solenopsis invicta diffusion data of the ecological activity range data to generate historical solenopsis invicta diffusion data; performing solenopsis invicta diffusion data analysis of the migration path according to the migration path data and the historical solenopsis invicta diffusion data, and generating migration path diffusion data; performing red fire ant prevention and control track design according to the migration path data and the migration path diffusion data to generate red fire ant prevention and control track data;
and the red fire ant prevention and control track optimization module is used for carrying out real-time optimization processing on the red fire ant prevention and control track data so as to generate optimized red fire ant prevention and control track data.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105023283A (en) * | 2015-06-24 | 2015-11-04 | 云南电网有限责任公司电力科学研究院 | Power grid bird trouble map drawing method and system based on winter visitor migration route and habitat |
| CN106940718A (en) * | 2017-03-14 | 2017-07-11 | 山东师范大学 | A kind of method, device and server for obtaining migratory bird moving path description |
| WO2023040539A1 (en) * | 2021-09-16 | 2023-03-23 | 腾讯科技（深圳）有限公司 | Vehicle stream relocating condition display method and apparatus, device, medium, and product |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105023283A (en) * | 2015-06-24 | 2015-11-04 | 云南电网有限责任公司电力科学研究院 | Power grid bird trouble map drawing method and system based on winter visitor migration route and habitat |
| CN106940718A (en) * | 2017-03-14 | 2017-07-11 | 山东师范大学 | A kind of method, device and server for obtaining migratory bird moving path description |
| WO2023040539A1 (en) * | 2021-09-16 | 2023-03-23 | 腾讯科技（深圳）有限公司 | Vehicle stream relocating condition display method and apparatus, device, medium, and product |
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