CN116227745A - Big data-based research and analysis method and system for fishing vessels - Google Patents
Big data-based research and analysis method and system for fishing vessels Download PDFInfo
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Abstract
The invention relates to the technical field of fishery resources, in particular to a large data-based research and analysis method and a large data-based research and analysis system for a fishing ship, which are used for obtaining a real-time environment influence factor set by acquiring actual parameter values of real-time environment factors of the fishing ship in the research process and analyzing the actual parameter values of the real-time environment factors; constructing a prediction model, guiding the real-time environment influence factor set into the prediction model for prediction to obtain preset operation parameters of the fish-involved ship, obtaining the real-time operation parameters of the fish-involved ship, and obtaining an abnormal operation parameter set based on the preset operation parameters and the real-time operation parameters; determining association anomaly equipment based on the performance information, investigation task information and anomaly operation parameter collection; and determining a corresponding regulation scheme based on the relevance abnormal equipment. The method can improve the operation effect of the fish-involved ship in the investigation process, so as to provide reliable data for fish resource analysis and maintenance.
Description
Technical Field
The invention relates to the technical field of fishery resources, in particular to a large data-based research and analysis method and a large data-based research and analysis system for a fishing ship.
Background
The regular development of the fishery resource investigation is an important project content for carrying out fish resource analysis and maintenance work, and the fishery fishing resource quantity is obtained through investigation, so that the annual change of the fishery fishing resource quantity is analyzed, and scientific basis can be provided for fishery management and fish resource protection. However, in the investigation and analysis process of the fishing vessels, the quantity of the fish gains is not only influenced by factors such as weather, fishing gear, operation time and duration, but also influenced by the performance of fishing vessel equipment and operation technology, so that the fish gains are greatly different, and the reliability of the fishery resource investigation is greatly influenced. In practical investigation, the difference of single-boat yield and variety among different fishing boats is larger, and the variety of fishes obtained from the same boat is often not more; the result obtained by investigation of a short term or a small number of fishing vessels is often inaccurate, and the time and economic cost of investigation are greatly increased by purchasing a large number of fishing vessels for a long term or a large number of fishing vessels, so that how to enable the fishing vessels to realize accurate operation in the investigation and analysis process of the fishing vessels is an important task to provide reliable data for the investigation of fishery resources.
Disclosure of Invention
The invention overcomes the defects of the prior art and provides a fishing ship investigation and analysis method and system based on big data.
The technical scheme adopted by the invention for achieving the purpose is as follows:
the invention discloses a large data-based research and analysis method for a fishing ship, which comprises the following steps:
acquiring actual parameter values of all real-time environmental factors of the fish-involved ships in the investigation process, and analyzing the actual parameter values of the real-time environmental factors to obtain a real-time environmental influence factor set;
constructing a prediction model, guiding the real-time environment influence factor set into the prediction model for prediction to obtain preset operation parameters of the fish-involved ship, obtaining the real-time operation parameters of the fish-involved ship, and obtaining an abnormal operation parameter set based on the preset operation parameters and the real-time operation parameters;
acquiring performance information and investigation task information of the fishing vessel, and determining association abnormal equipment based on the performance information, investigation task information and abnormal operation parameter collection;
and searching a big data network based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment appears in the investigation process of the fishing ship, screening the historical regulation scheme to obtain a regulation scheme corresponding to the highest regulation and control efficiency, and outputting the regulation scheme corresponding to the highest regulation and control efficiency.
Further, in a preferred embodiment of the present invention, actual parameter values of each real-time environmental factor of the fishing vessel in the investigation process are obtained, and the actual parameter values of the real-time environmental factors are analyzed to obtain a real-time environmental impact factor set, which specifically includes:
acquiring environmental factors influencing the investigation of the fishing vessels and corresponding influence thresholds thereof through a big data network, binding the environmental factors and the corresponding influence thresholds thereof to obtain environmental factor data packets, establishing a database, and importing the environmental factor data packets into the database to obtain a characteristic database;
acquiring actual parameter values of real-time environmental factors of the fish-involved ships in the investigation process, and importing the actual parameter values of the real-time environmental factors into the characteristic database so as to compare the actual parameter values of the real-time environmental factors with influence thresholds in corresponding environmental factor data packets;
and if the actual parameter value is larger than the corresponding influence threshold value, marking the real-time environment factors with the actual parameter value larger than the corresponding influence threshold value as real-time environment influence factors, and converging the real-time environment influence factors to obtain a real-time environment influence factor collection.
Further, in a preferred embodiment of the present invention, a prediction model is constructed, the real-time environmental impact factor set is imported into the prediction model to perform prediction, so as to obtain a preset operation parameter of the fish-involved ship, obtain the real-time operation parameter of the fish-involved ship, and obtain an abnormal operation parameter set based on the preset operation parameter and the real-time operation parameter, specifically:
acquiring normal operation parameters of the fish-involved ship under various environmental impact factor combination conditions through a big data network, constructing a prediction model based on a deep learning network, and importing the normal operation parameters of the fish-involved ship under various environmental impact factor combination conditions into the prediction model for training to obtain a trained prediction model;
the real-time environment influence factor set is imported into the trained prediction model to be predicted, and preset operation parameters of the fish-involved ship are obtained;
acquiring real-time operation parameters of the fish-involved ship, comparing the real-time operation parameters with preset operation parameters to obtain operation parameter deviation values, and comparing the operation parameter deviation values with the preset deviation values;
if the operating parameter deviation value is larger than the preset deviation value, marking the real-time operating parameter corresponding to the operating parameter deviation value larger than the preset deviation value as an abnormal operating parameter, and extracting and converging the abnormal operating parameter to obtain an abnormal operating parameter set.
Further, in a preferred embodiment of the present invention, performance information and investigation task information of the fishing vessel are obtained, and a relevance anomaly device is determined based on the performance information, investigation task information and anomaly operation parameter set, specifically:
acquiring performance information of the fish-involved ship, and calculating actual hash values between each abnormal operation parameter and the performance information through a hash method;
removing abnormal operation parameters with actual hash values not larger than a preset hash value from the abnormal operation parameter collection set, and reserving the abnormal operation parameters with actual hash values larger than the preset hash value from the abnormal operation parameter collection set to obtain a screened abnormal operation parameter collection set;
acquiring investigation task information of the fishing vessel, determining investigation indexes based on the investigation task information, performing association degree calculation on each abnormal operation parameter in the investigation indexes and the screened abnormal operation parameter set by a gray association analysis method, and acquiring the abnormal operation parameters with association degree larger than a preset association degree;
determining abnormal equipment which possibly affects the investigation task of the fishing vessel based on the abnormal operation parameters with the association degree larger than a preset association degree;
Inputting the abnormal equipment which possibly affects the investigation task of the fishing vessel into a Bayesian network for secondary simulation association to obtain the abnormal equipment which finally affects the investigation task of the fishing vessel, and marking the abnormal equipment which finally affects the investigation task of the fishing vessel as associated abnormal equipment output.
Further, in a preferred embodiment of the present invention, a big data network is searched based on the relevance abnormal equipment, so as to obtain a historical regulation scheme when the relevance abnormal equipment occurs in the investigation process of the fishing vessel, and the historical regulation scheme is screened, so as to obtain a regulation scheme corresponding to the highest regulation efficiency, and the regulation scheme corresponding to the highest regulation efficiency is output, specifically:
searching a big data network based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment appears in the investigation process of the fishing ship; the historical regulation and control schemes when the relevance abnormal equipment appears are collected to obtain an initial regulation and control scheme set, the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set is obtained, and the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set is compared with a preset threshold value;
If the initial regulation scheme sets have the regulation schemes with the regulation efficiency larger than the preset threshold value, extracting and collecting the regulation schemes with the regulation efficiency larger than the preset threshold value to obtain a regulation scheme set conforming to the regulation efficiency;
obtaining the regulation and control properties of all regulation and control schemes in the regulation and control scheme set conforming to the regulation and control efficiency, and removing the regulation and control scheme with the regulation and control properties being preset regulation and control properties from the regulation and control scheme set conforming to the regulation and control efficiency to obtain the regulation and control scheme set conforming to the regulation and control properties;
obtaining the regulation and control efficiency of each regulation and control scheme in the regulation and control scheme set conforming to the regulation and control property, constructing a first sequence table, guiding the regulation and control efficiency of each regulation and control scheme in the regulation and control scheme set conforming to the regulation and control property into the first sequence table for sequencing, extracting the highest regulation and control efficiency from the first sequence table after sequencing is completed, obtaining the regulation and control scheme corresponding to the highest regulation and control efficiency, and outputting the regulation and control scheme corresponding to the highest regulation and control efficiency.
Further, in a preferred embodiment of the present invention, the method further comprises the steps of:
if the initial regulation scheme set does not have the regulation scheme with the regulation efficiency larger than the preset threshold value, acquiring the regulation efficiency of each regulation scheme in the initial regulation scheme set;
Constructing a second sequence table, importing the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set into the second sequence table for sequencing, and extracting the maximum regulation and control efficiency from the second sequence table after sequencing is completed;
and obtaining a regulation scheme corresponding to the maximum regulation and control efficiency, and outputting the regulation and control scheme corresponding to the maximum regulation and control efficiency.
The invention further discloses a large data-based fishing vessel investigation and analysis system, which comprises a memory and a processor, wherein a fishing vessel investigation and analysis method program is stored in the memory, and when the fishing vessel investigation and analysis system is executed by the processor, the following steps are realized:
acquiring actual parameter values of all real-time environmental factors of the fish-involved ships in the investigation process, and analyzing the actual parameter values of the real-time environmental factors to obtain a real-time environmental influence factor set;
constructing a prediction model, guiding the real-time environment influence factor set into the prediction model for prediction to obtain preset operation parameters of the fish-involved ship, obtaining the real-time operation parameters of the fish-involved ship, and obtaining an abnormal operation parameter set based on the preset operation parameters and the real-time operation parameters;
Acquiring performance information and investigation task information of the fishing vessel, and determining association abnormal equipment based on the performance information, investigation task information and abnormal operation parameter collection;
and searching a big data network based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment appears in the investigation process of the fishing ship, screening the historical regulation scheme to obtain a regulation scheme corresponding to the highest regulation and control efficiency, and outputting the regulation scheme corresponding to the highest regulation and control efficiency.
Further, in a preferred embodiment of the present invention, actual parameter values of each real-time environmental factor of the fishing vessel in the investigation process are obtained, and the actual parameter values of the real-time environmental factors are analyzed to obtain a real-time environmental impact factor set, which specifically includes:
acquiring environmental factors influencing the investigation of the fishing vessels and corresponding influence thresholds thereof through a big data network, binding the environmental factors and the corresponding influence thresholds thereof to obtain environmental factor data packets, establishing a database, and importing the environmental factor data packets into the database to obtain a characteristic database;
Acquiring actual parameter values of real-time environmental factors of the fish-involved ships in the investigation process, and importing the actual parameter values of the real-time environmental factors into the characteristic database so as to compare the actual parameter values of the real-time environmental factors with influence thresholds in corresponding environmental factor data packets;
and if the actual parameter value is larger than the corresponding influence threshold value, marking the real-time environment factors with the actual parameter value larger than the corresponding influence threshold value as real-time environment influence factors, and converging the real-time environment influence factors to obtain a real-time environment influence factor collection.
Further, in a preferred embodiment of the present invention, performance information and investigation task information of the fishing vessel are obtained, and a relevance anomaly device is determined based on the performance information, investigation task information and anomaly operation parameter set, specifically:
acquiring performance information of the fish-involved ship, and calculating actual hash values between each abnormal operation parameter and the performance information through a hash method;
removing abnormal operation parameters with actual hash values not larger than a preset hash value from the abnormal operation parameter collection set, and reserving the abnormal operation parameters with actual hash values larger than the preset hash value from the abnormal operation parameter collection set to obtain a screened abnormal operation parameter collection set;
Acquiring investigation task information of the fishing vessel, determining investigation indexes based on the investigation task information, performing association degree calculation on each abnormal operation parameter in the investigation indexes and the screened abnormal operation parameter set by a gray association analysis method, and acquiring the abnormal operation parameters with association degree larger than a preset association degree;
determining abnormal equipment which possibly affects the investigation task of the fishing vessel based on the abnormal operation parameters with the association degree larger than a preset association degree;
inputting the abnormal equipment which possibly affects the investigation task of the fishing vessel into a Bayesian network for secondary simulation association to obtain the abnormal equipment which finally affects the investigation task of the fishing vessel, and marking the abnormal equipment which finally affects the investigation task of the fishing vessel as associated abnormal equipment output.
Further, in a preferred embodiment of the present invention, a big data network is searched based on the relevance abnormal equipment, so as to obtain a historical regulation scheme when the relevance abnormal equipment occurs in the investigation process of the fishing vessel, and the historical regulation scheme is screened, so as to obtain a regulation scheme corresponding to the highest regulation efficiency, and the regulation scheme corresponding to the highest regulation efficiency is output, specifically:
Searching a big data network based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment appears in the investigation process of the fishing ship; the historical regulation and control schemes when the relevance abnormal equipment appears are collected to obtain an initial regulation and control scheme set, the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set is obtained, and the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set is compared with a preset threshold value;
if the initial regulation scheme sets have the regulation schemes with the regulation efficiency larger than the preset threshold value, extracting and collecting the regulation schemes with the regulation efficiency larger than the preset threshold value to obtain a regulation scheme set conforming to the regulation efficiency;
obtaining the regulation and control properties of all regulation and control schemes in the regulation and control scheme set conforming to the regulation and control efficiency, and removing the regulation and control scheme with the regulation and control properties being preset regulation and control properties from the regulation and control scheme set conforming to the regulation and control efficiency to obtain the regulation and control scheme set conforming to the regulation and control properties;
obtaining the regulation and control efficiency of each regulation and control scheme in the regulation and control scheme set conforming to the regulation and control property, constructing a first sequence table, guiding the regulation and control efficiency of each regulation and control scheme in the regulation and control scheme set conforming to the regulation and control property into the first sequence table for sequencing, extracting the highest regulation and control efficiency from the first sequence table after sequencing is completed, obtaining the regulation and control scheme corresponding to the highest regulation and control efficiency, and outputting the regulation and control scheme corresponding to the highest regulation and control efficiency.
The invention solves the technical defects existing in the background technology, and has the following beneficial effects: analyzing the actual parameter values of the real-time environmental factors by acquiring the actual parameter values of the real-time environmental factors of the fish-involved ships in the investigation process to obtain a real-time environmental influence factor set; acquiring performance information and investigation task information of the fishing vessel, and determining association abnormal equipment based on the performance information, investigation task information and abnormal operation parameter collection; and determining a corresponding regulation scheme based on the relevance abnormal equipment. The method can improve the operation effect of the fish-involved ship in the investigation process, so as to provide reliable data for fish resource analysis and maintenance.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other embodiments of the drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is an overall method flow diagram of a large data based fishing vessel survey analysis method;
FIG. 2 is a flow chart of a first method of a method of analysis of a fishing vessel survey based on big data;
FIG. 3 is a second method flow diagram of a big data based method of investigation and analysis of a fishing vessel;
fig. 4 is a system block diagram of a large data based fishing vessel survey analysis system.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
The invention discloses a large data-based research and analysis method for a fishing ship, which is shown in fig. 1 and comprises the following steps:
s102: acquiring actual parameter values of all real-time environmental factors of the fish-involved ships in the investigation process, and analyzing the actual parameter values of the real-time environmental factors to obtain a real-time environmental influence factor set;
S104: constructing a prediction model, guiding the real-time environment influence factor set into the prediction model for prediction to obtain preset operation parameters of the fish-involved ship, obtaining the real-time operation parameters of the fish-involved ship, and obtaining an abnormal operation parameter set based on the preset operation parameters and the real-time operation parameters;
s106: acquiring performance information and investigation task information of the fishing vessel, and determining association abnormal equipment based on the performance information, investigation task information and abnormal operation parameter collection;
s108: and searching a big data network based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment appears in the investigation process of the fishing ship, screening the historical regulation scheme to obtain a regulation scheme corresponding to the highest regulation and control efficiency, and outputting the regulation scheme corresponding to the highest regulation and control efficiency.
In a preferred embodiment of the present invention, actual parameter values of each real-time environmental factor of the fishing vessel during investigation are obtained, and the actual parameter values of the real-time environmental factors are analyzed to obtain a real-time environmental impact factor set, as shown in fig. 2, specifically:
S202: acquiring environmental factors influencing the investigation of the fishing vessels and corresponding influence thresholds thereof through a big data network, binding the environmental factors and the corresponding influence thresholds thereof to obtain environmental factor data packets, establishing a database, and importing the environmental factor data packets into the database to obtain a characteristic database;
s204: acquiring actual parameter values of real-time environmental factors of the fish-involved ships in the investigation process, and importing the actual parameter values of the real-time environmental factors into the characteristic database so as to compare the actual parameter values of the real-time environmental factors with influence thresholds in corresponding environmental factor data packets;
s206: and if the actual parameter value is larger than the corresponding influence threshold value, marking the real-time environment factors with the actual parameter value larger than the corresponding influence threshold value as real-time environment influence factors, and converging the real-time environment influence factors to obtain a real-time environment influence factor collection.
It should be noted that, in the process of investigation operation of the fishing vessel, the operation effect of the fishing vessel is affected by environmental factors, for example, when the flow rate of the water body is too large, the difference between the fishing net and the set operation path and the operation shape is too large, so that the operation effect is affected, and the deviation is caused in the investigation obtained fishery resource data. The environmental factors include, but are not limited to, water flow rate, wind speed, water pressure, temperature and pressure, etc. The real-time environmental factors are screened by the method to obtain the real-time environmental influence factors influencing the current operation effect of the fishing vessels, so that the investigation analysis precision and reliability of the operation effect of the fishing vessels are improved.
In a preferred embodiment of the present invention, a prediction model is constructed, the real-time environmental impact factor set is imported into the prediction model for prediction, so as to obtain a preset operation parameter of the fish-involved ship, obtain the real-time operation parameter of the fish-involved ship, and obtain an abnormal operation parameter set based on the preset operation parameter and the real-time operation parameter, specifically:
acquiring normal operation parameters of the fish-involved ship under various environmental impact factor combination conditions through a big data network, constructing a prediction model based on a deep learning network, and importing the normal operation parameters of the fish-involved ship under various environmental impact factor combination conditions into the prediction model for training to obtain a trained prediction model;
the real-time environment influence factor set is imported into the trained prediction model to be predicted, and preset operation parameters of the fish-involved ship are obtained;
acquiring real-time operation parameters of the fish-involved ship, comparing the real-time operation parameters with preset operation parameters to obtain operation parameter deviation values, and comparing the operation parameter deviation values with the preset deviation values;
if the operating parameter deviation value is larger than the preset deviation value, marking the real-time operating parameter corresponding to the operating parameter deviation value larger than the preset deviation value as an abnormal operating parameter, and extracting and converging the abnormal operating parameter to obtain an abnormal operating parameter set.
It should be noted that, during the investigation operation of the fishing vessel, if the operation parameters of the fishing vessel are affected by one or more environmental impact factors, the operation parameters of the fishing vessel will change to a certain extent, and when the operation parameters change within a certain range of change, this is a normal situation. If the wind speed and temperature and pressure of the working environment suddenly increase when the fishing vessel is in operation, the working path of the fishing net can deviate to a certain extent, but the deviation degree is in a certain range, which belongs to a normal phenomenon, and the deviation degree range can be obtained from a big data network (namely, normal operation parameters). By the method, abnormal operation parameters of the fish-involved ship in the operation investigation process under the influence of the real-time environmental influence factors can be rapidly judged, so that equipment for predicting faults of the fish-involved ship in the operation investigation process is further analyzed, a corresponding regulation and control scheme is made, the operation investigation effect of the fish-involved ship is further ensured, and reliable data are provided for subsequent analysis of fishery resource quantity.
In a preferred embodiment of the present invention, performance information and investigation task information of the fishing vessel are obtained, and a relevance anomaly device is determined based on the performance information, investigation task information and anomaly operation parameter set, as shown in fig. 3, specifically:
S302: acquiring performance information of the fish-involved ship, and calculating actual hash values between each abnormal operation parameter and the performance information through a hash method;
s304: removing abnormal operation parameters with actual hash values not larger than a preset hash value from the abnormal operation parameter collection set, and reserving the abnormal operation parameters with actual hash values larger than the preset hash value from the abnormal operation parameter collection set to obtain a screened abnormal operation parameter collection set;
s306: acquiring investigation task information of the fishing vessel, determining investigation indexes based on the investigation task information, performing association degree calculation on each abnormal operation parameter in the investigation indexes and the screened abnormal operation parameter set by a gray association analysis method, and acquiring the abnormal operation parameters with association degree larger than a preset association degree;
s308: determining abnormal equipment which possibly affects the investigation task of the fishing vessel based on the abnormal operation parameters with the association degree larger than a preset association degree;
s310: inputting the abnormal equipment which possibly affects the investigation task of the fishing vessel into a Bayesian network for secondary simulation association to obtain the abnormal equipment which finally affects the investigation task of the fishing vessel, and marking the abnormal equipment which finally affects the investigation task of the fishing vessel as associated abnormal equipment output.
The performance information includes information on each equipment model in the fishing vessel, information on total operation time of the equipment, information on real-time evaluation report of the equipment, and the like. The investigation task information comprises a working path, a working precision grade, working time and the like of the investigation. After the abnormal operation parameters are determined, the abnormal operation parameters and equipment of the fishing vessel can be subjected to association analysis through the method, and the abnormal operation parameters which can influence the operation effect of the fishing vessel during operation are screened out by combining the performance information and investigation task information of the fishing vessel, so that the abnormal equipment which can influence the investigation effect of the fishing vessel is further determined, a corresponding regulation and control scheme is made according to the abnormal equipment, the operation investigation effect of the fishing vessel is further ensured, and reliable data is provided for the follow-up analysis of the fishery resource amount.
In a preferred embodiment of the present invention, a big data network is searched based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment occurs in the investigation process of the fishing ship, the historical regulation scheme is screened to obtain a regulation scheme corresponding to the highest regulation efficiency, and the regulation scheme corresponding to the highest regulation efficiency is output, specifically:
Searching a big data network based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment appears in the investigation process of the fishing ship; the historical regulation and control schemes when the relevance abnormal equipment appears are collected to obtain an initial regulation and control scheme set, the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set is obtained, and the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set is compared with a preset threshold value;
if the initial regulation scheme sets have the regulation schemes with the regulation efficiency larger than the preset threshold value, extracting and collecting the regulation schemes with the regulation efficiency larger than the preset threshold value to obtain a regulation scheme set conforming to the regulation efficiency;
obtaining the regulation and control properties of all regulation and control schemes in the regulation and control scheme set conforming to the regulation and control efficiency, and removing the regulation and control scheme with the regulation and control properties being preset regulation and control properties from the regulation and control scheme set conforming to the regulation and control efficiency to obtain the regulation and control scheme set conforming to the regulation and control properties;
obtaining the regulation and control efficiency of each regulation and control scheme in the regulation and control scheme set conforming to the regulation and control property, constructing a first sequence table, guiding the regulation and control efficiency of each regulation and control scheme in the regulation and control scheme set conforming to the regulation and control property into the first sequence table for sequencing, extracting the highest regulation and control efficiency from the first sequence table after sequencing is completed, obtaining the regulation and control scheme corresponding to the highest regulation and control efficiency, and outputting the regulation and control scheme corresponding to the highest regulation and control efficiency.
In a preferred embodiment of the present invention, the method further comprises the steps of:
if the initial regulation scheme set does not have the regulation scheme with the regulation efficiency larger than the preset threshold value, acquiring the regulation efficiency of each regulation scheme in the initial regulation scheme set;
constructing a second sequence table, importing the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set into the second sequence table for sequencing, and extracting the maximum regulation and control efficiency from the second sequence table after sequencing is completed;
and obtaining a regulation scheme corresponding to the maximum regulation and control efficiency, and outputting the regulation and control scheme corresponding to the maximum regulation and control efficiency.
It should be noted that, the preset regulation and control property is a regulation and control scheme needing manual regulation and control, a regulation and control scheme which is used when correlation abnormal equipment occurs in the investigation process of the fishing vessel is obtained through searching in a big data network, and the regulation and control scheme which is regulated and controlled to be higher than a preset threshold value is further screened, so that a regulation and control scheme with higher efficiency is obtained, then the regulation and control scheme needing manual regulation and control is removed from the regulation and control schemes with higher efficiency, for example, when the fishing net is greatly deviated, when a scheme needing manual correction exists in the past regulation and control scheme, the scheme needs to be removed. The method can generate a corresponding regulation and control scheme according to the relevance abnormal equipment information, and can exclude the artificial regulation and control scheme on the premise of ensuring regulation and control efficiency, thereby reducing the labor intensity of crews during investigation operation.
In addition, the method for investigation and analysis of the fishing ship based on big data further comprises the following steps:
acquiring signal receiving data information of the fish-involved ship during investigation operation in a preset time, determining a signal delay value based on the signal receiving data information, and comparing the signal delay value with a preset delay value to obtain delay deviation;
comparing the delay deviation with a preset deviation, and if the delay deviation is larger than the preset deviation, marking a investigation operation area corresponding to the delay deviation larger than the preset deviation as a signal transmission obstacle area;
acquiring the optimal receiving frequency of the signal receiving equipment under each climate factor parameter combination through a big data network, constructing a knowledge graph, and importing the optimal receiving frequency into the knowledge graph;
acquiring real-time climate factor parameters of a transmission obstacle region, and importing the real-time climate factor parameters into the knowledge graph to obtain a preset receiving frequency;
acquiring real-time receiving frequency of signal receiving equipment in the fishing vessel, and obtaining a frequency difference value based on the real-time receiving frequency and a preset receiving frequency;
and adjusting the real-time receiving frequency of the signal receiving equipment in the fishing vessel based on the frequency difference value.
It should be noted that, in the operation process of the fishing vessel, the receiving speed of the signal receiving device is affected by a climate factor, for example, the receiving speed of the signal receiving device is affected by too high temperature, so that the signal receiving delay phenomenon of the fishing vessel is caused, and when the signal receiving delay phenomenon occurs, the cooperative operation effect of the fishing vessels is affected.
In another aspect, the invention discloses a system for investigation and analysis of a fishing vessel based on big data, which comprises a memory 23 and a processor 24, wherein a program of investigation and analysis method of the fishing vessel is stored in the memory 23, and when the system is executed by the processor 24, as shown in fig. 4, the following steps are realized:
acquiring actual parameter values of all real-time environmental factors of the fish-involved ships in the investigation process, and analyzing the actual parameter values of the real-time environmental factors to obtain a real-time environmental influence factor set;
Constructing a prediction model, guiding the real-time environment influence factor set into the prediction model for prediction to obtain preset operation parameters of the fish-involved ship, obtaining the real-time operation parameters of the fish-involved ship, and obtaining an abnormal operation parameter set based on the preset operation parameters and the real-time operation parameters;
acquiring performance information and investigation task information of the fishing vessel, and determining association abnormal equipment based on the performance information, investigation task information and abnormal operation parameter collection;
and searching a big data network based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment appears in the investigation process of the fishing ship, screening the historical regulation scheme to obtain a regulation scheme corresponding to the highest regulation and control efficiency, and outputting the regulation scheme corresponding to the highest regulation and control efficiency.
Further, in a preferred embodiment of the present invention, actual parameter values of each real-time environmental factor of the fishing vessel in the investigation process are obtained, and the actual parameter values of the real-time environmental factors are analyzed to obtain a real-time environmental impact factor set, which specifically includes:
acquiring environmental factors influencing the investigation of the fishing vessels and corresponding influence thresholds thereof through a big data network, binding the environmental factors and the corresponding influence thresholds thereof to obtain environmental factor data packets, establishing a database, and importing the environmental factor data packets into the database to obtain a characteristic database;
Acquiring actual parameter values of real-time environmental factors of the fish-involved ships in the investigation process, and importing the actual parameter values of the real-time environmental factors into the characteristic database so as to compare the actual parameter values of the real-time environmental factors with influence thresholds in corresponding environmental factor data packets;
and if the actual parameter value is larger than the corresponding influence threshold value, marking the real-time environment factors with the actual parameter value larger than the corresponding influence threshold value as real-time environment influence factors, and converging the real-time environment influence factors to obtain a real-time environment influence factor collection.
Further, in a preferred embodiment of the present invention, performance information and investigation task information of the fishing vessel are obtained, and a relevance anomaly device is determined based on the performance information, investigation task information and anomaly operation parameter set, specifically:
acquiring performance information of the fish-involved ship, and calculating actual hash values between each abnormal operation parameter and the performance information through a hash method;
removing abnormal operation parameters with actual hash values not larger than a preset hash value from the abnormal operation parameter collection set, and reserving the abnormal operation parameters with actual hash values larger than the preset hash value from the abnormal operation parameter collection set to obtain a screened abnormal operation parameter collection set;
Acquiring investigation task information of the fishing vessel, determining investigation indexes based on the investigation task information, performing association degree calculation on each abnormal operation parameter in the investigation indexes and the screened abnormal operation parameter set by a gray association analysis method, and acquiring the abnormal operation parameters with association degree larger than a preset association degree;
determining abnormal equipment which possibly affects the investigation task of the fishing vessel based on the abnormal operation parameters with the association degree larger than a preset association degree;
inputting the abnormal equipment which possibly affects the investigation task of the fishing vessel into a Bayesian network for secondary simulation association to obtain the abnormal equipment which finally affects the investigation task of the fishing vessel, and marking the abnormal equipment which finally affects the investigation task of the fishing vessel as associated abnormal equipment output.
Further, in a preferred embodiment of the present invention, a big data network is searched based on the relevance abnormal equipment, so as to obtain a historical regulation scheme when the relevance abnormal equipment occurs in the investigation process of the fishing vessel, and the historical regulation scheme is screened, so as to obtain a regulation scheme corresponding to the highest regulation efficiency, and the regulation scheme corresponding to the highest regulation efficiency is output, specifically:
Searching a big data network based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment appears in the investigation process of the fishing ship; the historical regulation and control schemes when the relevance abnormal equipment appears are collected to obtain an initial regulation and control scheme set, the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set is obtained, and the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set is compared with a preset threshold value;
if the initial regulation scheme sets have the regulation schemes with the regulation efficiency larger than the preset threshold value, extracting and collecting the regulation schemes with the regulation efficiency larger than the preset threshold value to obtain a regulation scheme set conforming to the regulation efficiency;
obtaining the regulation and control properties of all regulation and control schemes in the regulation and control scheme set conforming to the regulation and control efficiency, and removing the regulation and control scheme with the regulation and control properties being preset regulation and control properties from the regulation and control scheme set conforming to the regulation and control efficiency to obtain the regulation and control scheme set conforming to the regulation and control properties;
obtaining the regulation and control efficiency of each regulation and control scheme in the regulation and control scheme set conforming to the regulation and control property, constructing a first sequence table, guiding the regulation and control efficiency of each regulation and control scheme in the regulation and control scheme set conforming to the regulation and control property into the first sequence table for sequencing, extracting the highest regulation and control efficiency from the first sequence table after sequencing is completed, obtaining the regulation and control scheme corresponding to the highest regulation and control efficiency, and outputting the regulation and control scheme corresponding to the highest regulation and control efficiency.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
The foregoing is merely illustrative embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think about variations or substitutions within the technical scope of the present invention, and the invention should be covered. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (10)
1. The research and analysis method of the fishing ship based on big data is characterized by comprising the following steps:
acquiring actual parameter values of all real-time environmental factors of the fish-involved ships in the investigation process, and analyzing the actual parameter values of the real-time environmental factors to obtain a real-time environmental influence factor set;
constructing a prediction model, guiding the real-time environment influence factor set into the prediction model for prediction to obtain preset operation parameters of the fish-involved ship, obtaining the real-time operation parameters of the fish-involved ship, and obtaining an abnormal operation parameter set based on the preset operation parameters and the real-time operation parameters;
acquiring performance information and investigation task information of the fishing vessel, and determining association abnormal equipment based on the performance information, investigation task information and abnormal operation parameter collection;
And searching a big data network based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment appears in the investigation process of the fishing ship, screening the historical regulation scheme to obtain a regulation scheme corresponding to the highest regulation and control efficiency, and outputting the regulation scheme corresponding to the highest regulation and control efficiency.
2. The method for investigation and analysis of fishing vessels based on big data according to claim 1, wherein the method is characterized in that the actual parameter values of each real-time environmental factor of the fishing vessels in the investigation process are obtained, and the actual parameter values of the real-time environmental factors are analyzed to obtain a real-time environmental influence factor set, specifically:
acquiring environmental factors influencing the investigation of the fishing vessels and corresponding influence thresholds thereof through a big data network, binding the environmental factors and the corresponding influence thresholds thereof to obtain environmental factor data packets, establishing a database, and importing the environmental factor data packets into the database to obtain a characteristic database;
acquiring actual parameter values of real-time environmental factors of the fish-involved ships in the investigation process, and importing the actual parameter values of the real-time environmental factors into the characteristic database so as to compare the actual parameter values of the real-time environmental factors with influence thresholds in corresponding environmental factor data packets;
And if the actual parameter value is larger than the corresponding influence threshold value, marking the real-time environment factors with the actual parameter value larger than the corresponding influence threshold value as real-time environment influence factors, and converging the real-time environment influence factors to obtain a real-time environment influence factor collection.
3. The method for investigation and analysis of the fishing vessel based on big data according to claim 1, wherein a prediction model is constructed, the real-time environmental impact factor set is imported into the prediction model for prediction to obtain a preset operation parameter of the fishing vessel, the real-time operation parameter of the fishing vessel is obtained, and an abnormal operation parameter set is obtained based on the preset operation parameter and the real-time operation parameter, specifically:
acquiring normal operation parameters of the fish-involved ship under various environmental impact factor combination conditions through a big data network, constructing a prediction model based on a deep learning network, and importing the normal operation parameters of the fish-involved ship under various environmental impact factor combination conditions into the prediction model for training to obtain a trained prediction model;
the real-time environment influence factor set is imported into the trained prediction model to be predicted, and preset operation parameters of the fish-involved ship are obtained;
Acquiring real-time operation parameters of the fish-involved ship, comparing the real-time operation parameters with preset operation parameters to obtain operation parameter deviation values, and comparing the operation parameter deviation values with the preset deviation values;
if the operating parameter deviation value is larger than the preset deviation value, marking the real-time operating parameter corresponding to the operating parameter deviation value larger than the preset deviation value as an abnormal operating parameter, and extracting and converging the abnormal operating parameter to obtain an abnormal operating parameter set.
4. The method for investigation and analysis of fishing vessels based on big data according to claim 1, wherein performance information and investigation task information of the fishing vessels are obtained, and correlation anomaly equipment is determined based on the performance information, investigation task information and anomaly operation parameter set, specifically:
acquiring performance information of the fish-involved ship, and calculating actual hash values between each abnormal operation parameter and the performance information through a hash method;
removing abnormal operation parameters with actual hash values not larger than a preset hash value from the abnormal operation parameter collection set, and reserving the abnormal operation parameters with actual hash values larger than the preset hash value from the abnormal operation parameter collection set to obtain a screened abnormal operation parameter collection set;
Acquiring investigation task information of the fishing vessel, determining investigation indexes based on the investigation task information, performing association degree calculation on each abnormal operation parameter in the investigation indexes and the screened abnormal operation parameter set by a gray association analysis method, and acquiring the abnormal operation parameters with association degree larger than a preset association degree;
determining abnormal equipment which possibly affects the investigation task of the fishing vessel based on the abnormal operation parameters with the association degree larger than a preset association degree;
inputting the abnormal equipment which possibly affects the investigation task of the fishing vessel into a Bayesian network for secondary simulation association to obtain the abnormal equipment which finally affects the investigation task of the fishing vessel, and marking the abnormal equipment which finally affects the investigation task of the fishing vessel as associated abnormal equipment output.
5. The method for investigation and analysis of fishing vessels based on big data according to claim 1, wherein the method is characterized in that a big data network is searched based on the relevance anomaly equipment to obtain a historical regulation scheme when the relevance anomaly equipment occurs in the investigation process of the fishing vessels, the historical regulation scheme is screened to obtain a regulation scheme corresponding to the highest regulation and control efficiency, and the regulation scheme corresponding to the highest regulation and control efficiency is output, specifically:
Searching a big data network based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment appears in the investigation process of the fishing ship; the historical regulation and control schemes when the relevance abnormal equipment appears are collected to obtain an initial regulation and control scheme set, the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set is obtained, and the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set is compared with a preset threshold value;
if the initial regulation scheme sets have the regulation schemes with the regulation efficiency larger than the preset threshold value, extracting and collecting the regulation schemes with the regulation efficiency larger than the preset threshold value to obtain a regulation scheme set conforming to the regulation efficiency;
obtaining the regulation and control properties of all regulation and control schemes in the regulation and control scheme set conforming to the regulation and control efficiency, and removing the regulation and control scheme with the regulation and control properties being preset regulation and control properties from the regulation and control scheme set conforming to the regulation and control efficiency to obtain the regulation and control scheme set conforming to the regulation and control properties;
obtaining the regulation and control efficiency of each regulation and control scheme in the regulation and control scheme set conforming to the regulation and control property, constructing a first sequence table, guiding the regulation and control efficiency of each regulation and control scheme in the regulation and control scheme set conforming to the regulation and control property into the first sequence table for sequencing, extracting the highest regulation and control efficiency from the first sequence table after sequencing is completed, obtaining the regulation and control scheme corresponding to the highest regulation and control efficiency, and outputting the regulation and control scheme corresponding to the highest regulation and control efficiency.
6. The method for analyzing the research on the fishing vessels based on big data according to claim 5, further comprising the steps of:
if the initial regulation scheme set does not have the regulation scheme with the regulation efficiency larger than the preset threshold value, acquiring the regulation efficiency of each regulation scheme in the initial regulation scheme set;
constructing a second sequence table, importing the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set into the second sequence table for sequencing, and extracting the maximum regulation and control efficiency from the second sequence table after sequencing is completed;
and obtaining a regulation scheme corresponding to the maximum regulation and control efficiency, and outputting the regulation and control scheme corresponding to the maximum regulation and control efficiency.
7. The fishing vessel investigation and analysis system based on big data is characterized by comprising a memory and a processor, wherein a fishing vessel investigation and analysis method program is stored in the memory, and when the fishing vessel investigation and analysis system is executed by the processor, the following steps are realized:
acquiring actual parameter values of all real-time environmental factors of the fish-involved ships in the investigation process, and analyzing the actual parameter values of the real-time environmental factors to obtain a real-time environmental influence factor set;
Constructing a prediction model, guiding the real-time environment influence factor set into the prediction model for prediction to obtain preset operation parameters of the fish-involved ship, obtaining the real-time operation parameters of the fish-involved ship, and obtaining an abnormal operation parameter set based on the preset operation parameters and the real-time operation parameters;
acquiring performance information and investigation task information of the fishing vessel, and determining association abnormal equipment based on the performance information, investigation task information and abnormal operation parameter collection;
and searching a big data network based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment appears in the investigation process of the fishing ship, screening the historical regulation scheme to obtain a regulation scheme corresponding to the highest regulation and control efficiency, and outputting the regulation scheme corresponding to the highest regulation and control efficiency.
8. The big data-based fish-involved ship investigation analysis system of claim 7, wherein the real parameter values of each real-time environmental factor of the fish-involved ship in the investigation process are obtained, and the real parameter values of the real-time environmental factors are analyzed to obtain a real-time environmental impact factor set, specifically:
Acquiring environmental factors influencing the investigation of the fishing vessels and corresponding influence thresholds thereof through a big data network, binding the environmental factors and the corresponding influence thresholds thereof to obtain environmental factor data packets, establishing a database, and importing the environmental factor data packets into the database to obtain a characteristic database;
acquiring actual parameter values of real-time environmental factors of the fish-involved ships in the investigation process, and importing the actual parameter values of the real-time environmental factors into the characteristic database so as to compare the actual parameter values of the real-time environmental factors with influence thresholds in corresponding environmental factor data packets;
and if the actual parameter value is larger than the corresponding influence threshold value, marking the real-time environment factors with the actual parameter value larger than the corresponding influence threshold value as real-time environment influence factors, and converging the real-time environment influence factors to obtain a real-time environment influence factor collection.
9. The big data-based research analysis system of a fishing vessel according to claim 7, wherein performance information and research mission information of the fishing vessel are obtained, and the relevance anomaly device is determined based on the performance information, the research mission information and the anomaly operation parameter set, specifically:
Acquiring performance information of the fish-involved ship, and calculating actual hash values between each abnormal operation parameter and the performance information through a hash method;
removing abnormal operation parameters with actual hash values not larger than a preset hash value from the abnormal operation parameter collection set, and reserving the abnormal operation parameters with actual hash values larger than the preset hash value from the abnormal operation parameter collection set to obtain a screened abnormal operation parameter collection set;
acquiring investigation task information of the fishing vessel, determining investigation indexes based on the investigation task information, performing association degree calculation on each abnormal operation parameter in the investigation indexes and the screened abnormal operation parameter set by a gray association analysis method, and acquiring the abnormal operation parameters with association degree larger than a preset association degree;
determining abnormal equipment which possibly affects the investigation task of the fishing vessel based on the abnormal operation parameters with the association degree larger than a preset association degree;
inputting the abnormal equipment which possibly affects the investigation task of the fishing vessel into a Bayesian network for secondary simulation association to obtain the abnormal equipment which finally affects the investigation task of the fishing vessel, and marking the abnormal equipment which finally affects the investigation task of the fishing vessel as associated abnormal equipment output.
10. The big data-based research analysis system of a fishing vessel according to claim 7, wherein the big data network is searched based on the relevance anomaly device to obtain a historical regulation scheme when the relevance anomaly device appears in the research process of the fishing vessel, the historical regulation scheme is screened to obtain a regulation scheme corresponding to the highest regulation and control efficiency, and the regulation scheme corresponding to the highest regulation and control efficiency is output, specifically:
searching a big data network based on the relevance abnormal equipment to obtain a historical regulation scheme when the relevance abnormal equipment appears in the investigation process of the fishing ship; the historical regulation and control schemes when the relevance abnormal equipment appears are collected to obtain an initial regulation and control scheme set, the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set is obtained, and the regulation and control efficiency of each regulation and control scheme in the initial regulation and control scheme set is compared with a preset threshold value;
if the initial regulation scheme sets have the regulation schemes with the regulation efficiency larger than the preset threshold value, extracting and collecting the regulation schemes with the regulation efficiency larger than the preset threshold value to obtain a regulation scheme set conforming to the regulation efficiency;
Obtaining the regulation and control properties of all regulation and control schemes in the regulation and control scheme set conforming to the regulation and control efficiency, and removing the regulation and control scheme with the regulation and control properties being preset regulation and control properties from the regulation and control scheme set conforming to the regulation and control efficiency to obtain the regulation and control scheme set conforming to the regulation and control properties;
obtaining the regulation and control efficiency of each regulation and control scheme in the regulation and control scheme set conforming to the regulation and control property, constructing a first sequence table, guiding the regulation and control efficiency of each regulation and control scheme in the regulation and control scheme set conforming to the regulation and control property into the first sequence table for sequencing, extracting the highest regulation and control efficiency from the first sequence table after sequencing is completed, obtaining the regulation and control scheme corresponding to the highest regulation and control efficiency, and outputting the regulation and control scheme corresponding to the highest regulation and control efficiency.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116735848A (en) * | 2023-07-20 | 2023-09-12 | 广东博创佳禾科技有限公司 | Sample detection device and control method thereof |
| CN116842322A (en) * | 2023-07-19 | 2023-10-03 | 深圳市精微康投资发展有限公司 | Electric motor operation optimization method and system based on data processing |
| CN117493791A (en) * | 2023-10-10 | 2024-02-02 | 交通运输部东海航海保障中心温州航标处 | Marine navigation mark monitoring and evaluating method and system based on data analysis |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2539020A (en) * | 2015-06-04 | 2016-12-07 | Bae Systems Plc | Decision making |
| CN108313236A (en) * | 2018-01-24 | 2018-07-24 | 深圳远航股份有限公司 | A kind of ship's navigation method for early warning and system |
| CN110516972A (en) * | 2019-08-30 | 2019-11-29 | 哈尔滨工程大学 | A kind of ship sails and operation on the sea comprehensive forecasting assessment system |
| KR20200118631A (en) * | 2019-04-08 | 2020-10-16 | 대구한의대학교산학협력단 | Shipping liner operational manageability estimation method for resilient port operations |
| CN112464951A (en) * | 2020-11-24 | 2021-03-09 | 中国水产科学研究院南海水产研究所 | Fishery safety emergency disposal system and method based on Internet of things |
| CN112578725A (en) * | 2020-12-16 | 2021-03-30 | 中国水产科学研究院南海水产研究所 | Fishery water aquaculture facility safety early warning system and method based on Internet of things |
| CN113379137A (en) * | 2021-06-21 | 2021-09-10 | 中国海洋大学 | Method, system, storage medium and terminal for modeling and predicting fishing boat operation area |
| CN113537639A (en) * | 2021-08-16 | 2021-10-22 | 华中农业大学 | Method and system for establishing fish growth prediction model as culture environment parameter |
| CN114384821A (en) * | 2021-12-17 | 2022-04-22 | 武汉理工大学 | Ship motion model processing method and device and storage medium |
| CN115248824A (en) * | 2022-08-04 | 2022-10-28 | 中国水产科学研究院南海水产研究所 | Ocean fishery safety early warning method, system and medium based on big data |
-
2023
- 2023-05-06 CN CN202310502101.8A patent/CN116227745B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2539020A (en) * | 2015-06-04 | 2016-12-07 | Bae Systems Plc | Decision making |
| CN108313236A (en) * | 2018-01-24 | 2018-07-24 | 深圳远航股份有限公司 | A kind of ship's navigation method for early warning and system |
| KR20200118631A (en) * | 2019-04-08 | 2020-10-16 | 대구한의대학교산학협력단 | Shipping liner operational manageability estimation method for resilient port operations |
| CN110516972A (en) * | 2019-08-30 | 2019-11-29 | 哈尔滨工程大学 | A kind of ship sails and operation on the sea comprehensive forecasting assessment system |
| CN112464951A (en) * | 2020-11-24 | 2021-03-09 | 中国水产科学研究院南海水产研究所 | Fishery safety emergency disposal system and method based on Internet of things |
| CN112578725A (en) * | 2020-12-16 | 2021-03-30 | 中国水产科学研究院南海水产研究所 | Fishery water aquaculture facility safety early warning system and method based on Internet of things |
| CN113379137A (en) * | 2021-06-21 | 2021-09-10 | 中国海洋大学 | Method, system, storage medium and terminal for modeling and predicting fishing boat operation area |
| CN113537639A (en) * | 2021-08-16 | 2021-10-22 | 华中农业大学 | Method and system for establishing fish growth prediction model as culture environment parameter |
| CN114384821A (en) * | 2021-12-17 | 2022-04-22 | 武汉理工大学 | Ship motion model processing method and device and storage medium |
| CN115248824A (en) * | 2022-08-04 | 2022-10-28 | 中国水产科学研究院南海水产研究所 | Ocean fishery safety early warning method, system and medium based on big data |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116842322A (en) * | 2023-07-19 | 2023-10-03 | 深圳市精微康投资发展有限公司 | Electric motor operation optimization method and system based on data processing |
| CN116842322B (en) * | 2023-07-19 | 2024-02-23 | 深圳市精微康投资发展有限公司 | Electric motor operation optimization method and system based on data processing |
| CN116735848A (en) * | 2023-07-20 | 2023-09-12 | 广东博创佳禾科技有限公司 | Sample detection device and control method thereof |
| CN116735848B (en) * | 2023-07-20 | 2024-05-28 | 上海拜谱生物科技有限公司 | Sample detection device and control method thereof |
| CN117493791A (en) * | 2023-10-10 | 2024-02-02 | 交通运输部东海航海保障中心温州航标处 | Marine navigation mark monitoring and evaluating method and system based on data analysis |
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|---|---|
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