CN114997546A - Comprehensive survey evaluation method, system and medium for monitoring well based on multi-source data - Google Patents
Comprehensive survey evaluation method, system and medium for monitoring well based on multi-source data Download PDFInfo
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Abstract
The invention discloses a monitoring well comprehensive investigation evaluation method, system and medium based on multi-source data, which comprises the following steps: acquiring influence factors of underground water environment monitoring precision of the monitoring well through big data retrieval, screening the influence factors, selecting a data source according to the screened influence factors to acquire survey data of the monitoring well, and performing comprehensive evaluation on the monitoring well by combining the survey data with basic information of the monitoring well through a fuzzy comprehensive evaluation method; judging the monitoring performance of the monitoring wells according to the comprehensive evaluation of the monitoring wells and generating maintenance suggestions according to the monitoring performance of each monitoring well; and screening the monitoring wells according to whether the monitoring wells have the monitoring function or not based on the comprehensive evaluation result of the single monitoring well in the target area, and performing distribution optimization of the monitoring wells according to the distribution of the screened monitoring wells and the pollution source information. According to the invention, the monitoring performance of the monitoring well and the basic condition and the distribution characteristic are evaluated by selecting the adaptive evaluation index to generate the maintenance basis, so that the construction and maintenance cost of the monitoring well is saved.
Description
Technical Field
The invention relates to the technical field of survey evaluation of monitoring wells, in particular to a comprehensive survey evaluation method, a comprehensive survey evaluation system and a comprehensive survey evaluation medium for monitoring wells based on multi-source data.
Background
The underground water environment monitoring well is used as an important support for carrying out underground water environment monitoring work, and the health condition of the underground water environment monitoring well directly influences the accuracy of a monitoring result. Due to the lack of professional knowledge and the fact that a management department does not set a maintenance and management method of a system, the phenomena that maintenance and management work is not in place in the later period, monitoring functions are lost and the like exist in part of monitoring wells, even the monitoring wells become polluted channels, the monitoring wells which are still running need to be evaluated urgently to judge whether underground water monitoring work requirements can be met, and inspection maintenance and unified management are enhanced according to evaluation results.
The method has the advantages that the well casing damage, the water filter pipe blockage, the plugging of foreign matters in the well casing, excessive sedimentation and the like easily occur to the monitoring well in the continuous operation of the long-term monitoring well, so that the hydraulic connection between the inside and the outside of the well is poor, the collected underground water sample has no representative condition, and the standard judgment cannot be carried out due to different forms and different storage conditions of the monitoring well in the evaluation of the underground water environment monitoring well under the condition. Therefore, a proper evaluation index is selected, and an applicable evaluation method is formulated to provide basic technical support for perfecting a groundwater environment monitoring system, strengthening potential pollution source monitoring, improving groundwater environment monitoring capability and groundwater environment risk prevention and control.
Disclosure of Invention
In order to solve at least one technical problem, the invention provides a monitoring well comprehensive survey evaluation method, a monitoring well comprehensive survey evaluation system and a monitoring well comprehensive survey evaluation medium based on multi-source data.
The invention provides a monitoring well comprehensive investigation evaluation method based on multi-source data, which comprises the following steps:
acquiring influence factors of underground water environment monitoring precision of the monitoring well through big data retrieval, screening the influence factors, and selecting a data source according to the screened influence factors;
acquiring survey data of the monitoring well according to the data source, and carrying out comprehensive evaluation on the monitoring well by combining the survey data with basic information of the monitoring well through a fuzzy comprehensive evaluation method;
judging the monitoring performance of the monitoring wells according to the comprehensive evaluation of the monitoring wells and generating maintenance suggestions according to the monitoring performance of each monitoring well;
and screening the monitoring wells according to whether the monitoring wells have the monitoring function or not based on the comprehensive evaluation result of the single monitoring well in the target area, and performing distribution optimization of the monitoring wells according to the distribution of the screened monitoring wells and the pollution source information.
In this scheme, obtain the influence factor of the groundwater environment monitoring precision of monitoring well through big data retrieval, specifically do:
setting keyword information through an underground water environment monitoring well and monitoring precision, obtaining related resource data through big data retrieval according to the keyword information, and selecting influence factors related to the state of the monitoring well through the related resource data to construct a knowledge graph;
generating a nondirectional heterogeneous graph between monitoring precision and influence factors of the monitoring well according to the knowledge graph, and performing coding learning on the nondirectional heterogeneous graph through a graph convolution neural network;
acquiring a low-dimensional vector of the monitoring precision and the influence factors as an initial feature vector, and acquiring a final vector representation of the monitoring precision and the influence factors through neighbor node aggregation and an attention mechanism;
obtaining scores of monitoring precision on the influence factors through vector inner products, generating a reverse ordering result according to the scores, selecting a preset number of influence factors according to the reverse ordering result, and obtaining investigation data of all the influence factors.
In the scheme, the survey data is combined with basic information of the monitoring well to carry out comprehensive evaluation on the monitoring well by a fuzzy comprehensive evaluation method, and the method specifically comprises the following steps:
determining an evaluation index according to the screened influence factors, and generating weight information of the evaluation index according to the scores of the influence factors;
forming a factor set of fuzzy comprehensive evaluation according to the evaluation indexes, setting an evaluation set of monitoring well performance evaluation, obtaining the membership of each evaluation index to each element in the evaluation set through monitoring well basic information and survey data, and generating a membership matrix;
acquiring fuzzy comprehensive evaluation results according to the membership matrix and the weight information, and grading the monitoring wells according to the fuzzy comprehensive evaluation results of all the monitoring wells in the target area;
and acquiring the scrapped monitoring wells in the target area according to the grading result, and marking according to the position information of the scrapped monitoring wells.
In this scheme, judge the monitoring performance of monitoring well and according to the monitoring performance generation maintenance suggestion of each monitoring well according to monitoring well comprehensive evaluation, specifically do:
acquiring fuzzy comprehensive evaluation results of all monitoring wells in a target area and evaluation results of single evaluation indexes in the fuzzy comprehensive evaluation;
acquiring the monitoring well of which the fuzzy comprehensive evaluation result is greater than a preset threshold value for judgment, selecting an evaluation index related to the monitoring performance of the monitoring well, presetting a threshold range and a grading standard of the related evaluation index, and judging whether the related evaluation index of the monitoring well in the target area is in the corresponding threshold range;
if at least one evaluation index of the monitoring well is not in the corresponding threshold range, generating maintenance information of the monitoring well, and acquiring an unqualified evaluation index set of the monitoring well;
acquiring the repair items of the monitoring well through the non-standard evaluation set, acquiring the scores of the repair items according to the threshold range of the evaluation indexes and the corresponding score standards, and judging the repairability of the repair items according to the scores;
and screening repairable repair items according to the repairability, and generating maintenance suggestions through similar historical repair cases.
In this scheme, whether the comprehensive evaluation result based on single monitoring well in the target area possesses the monitoring function according to screening the monitoring well, specifically do:
acquiring information of the scrapped monitoring wells according to the comprehensive evaluation result of the single monitoring well in the target area, and judging whether the number of the non-standard evaluation indexes in the non-standard evaluation index set of each monitoring well is larger than a preset number threshold value or not;
judging the monitoring wells with the number of the scrapped monitoring wells or the monitoring wells with the number of the substandard evaluation indexes larger than a preset number threshold value as the monitoring wells without the monitoring function;
according to the repairability of the monitoring well repairing project, representing the monitoring performance predicted value of the monitoring well within the preset time, and classifying the monitoring well with the monitoring performance predicted value smaller than the preset prediction threshold value as a monitoring well without the monitoring function;
and marking the monitoring well without the monitoring function in the target area.
In this scheme, combine pollution sources information to carry out the stationing optimization of monitoring well according to the distribution of the monitoring well after the screening, specifically do:
removing the monitoring wells marked in the target area, acquiring pollution source information in the target area, and dividing the target area into a plurality of sub-areas according to the pollution source information;
when the number information of the monitoring wells with the monitoring function in the sub-area is smaller than a preset threshold value, performing point distribution optimization on the monitoring wells;
calculating the mean square distance information between monitoring wells in the sub-area, constructing a monitoring well optimization model based on a neural network of a genetic algorithm, and taking the mean square distance between the monitoring wells as a fitness function;
and generating position information of the newly added monitoring well through a monitoring well optimization model according to the hydrogeological information of the target area and the position information of the existing monitoring well in the sub-area.
The invention also provides a monitoring well comprehensive investigation and evaluation system based on multi-source data, which comprises: the monitoring well comprehensive investigation and evaluation method based on the multi-source data comprises a memory and a processor, wherein the memory comprises a monitoring well comprehensive investigation and evaluation method program based on the multi-source data, and the monitoring well comprehensive investigation and evaluation method program based on the multi-source data realizes the following steps when being executed by the processor:
acquiring influence factors of underground water environment monitoring precision of the monitoring well through big data retrieval, screening the influence factors, and selecting a data source according to the screened influence factors;
acquiring survey data of the monitoring well according to the data source, and carrying out comprehensive evaluation on the monitoring well by combining the survey data with basic information of the monitoring well through a fuzzy comprehensive evaluation method;
judging the monitoring performance of the monitoring wells according to the comprehensive evaluation of the monitoring wells and generating maintenance suggestions according to the monitoring performance of each monitoring well;
and screening the monitoring wells according to whether the monitoring wells have the monitoring function or not based on the comprehensive evaluation result of the single monitoring well in the target area, and performing distribution optimization of the monitoring wells according to the distribution of the screened monitoring wells and the pollution source information.
The third aspect of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a program of a comprehensive survey evaluation method for a monitoring well based on multi-source data, and when the program of the comprehensive survey evaluation method for the monitoring well based on multi-source data is executed by a processor, the steps of the comprehensive survey evaluation method for the monitoring well based on multi-source data as described in any one of the above are implemented.
The invention discloses a monitoring well comprehensive survey evaluation method, a monitoring well comprehensive survey evaluation system and a monitoring well comprehensive survey evaluation medium based on multi-source data, wherein the monitoring well comprehensive survey evaluation method comprises the following steps: acquiring influence factors of underground water environment monitoring precision of the monitoring well through big data retrieval, screening the influence factors, selecting a data source according to the screened influence factors to acquire survey data of the monitoring well, and performing comprehensive evaluation on the monitoring well by combining the survey data with basic information of the monitoring well through a fuzzy comprehensive evaluation method; judging the monitoring performance of the monitoring wells according to the comprehensive evaluation of the monitoring wells and generating maintenance suggestions according to the monitoring performance of each monitoring well; and screening the monitoring wells according to whether the monitoring wells have the monitoring function or not based on the comprehensive evaluation result of the single monitoring well in the target area, and performing distribution optimization of the monitoring wells according to the distribution of the screened monitoring wells and the pollution source information. According to the invention, the monitoring performance of the monitoring well and the basic condition and the distribution characteristic are evaluated by selecting the adaptive evaluation index to generate the maintenance basis, so that the construction and maintenance cost of the monitoring well is saved.
Drawings
FIG. 1 shows a flow chart of a comprehensive survey evaluation method for a monitoring well based on multi-source data according to the invention;
FIG. 2 is a flow chart illustrating a method of determining an evaluation index according to the present invention;
FIG. 3 illustrates a flow chart of a method for comprehensive evaluation of a monitoring well according to the present invention;
FIG. 4 shows a block diagram of a comprehensive survey evaluation system for a monitoring well based on multi-source data.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention, taken in conjunction with the accompanying drawings and detailed description, is set forth below. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
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 specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
FIG. 1 shows a flow chart of a comprehensive survey evaluation method for a monitoring well based on multi-source data.
As shown in fig. 1, a first aspect of the present invention provides a monitoring well comprehensive investigation evaluation method based on multi-source data, including:
s102, acquiring influence factors of underground water environment monitoring precision of the monitoring well through big data retrieval, screening the influence factors, and selecting a data source according to the screened influence factors;
s104, acquiring survey data of the monitoring well according to the data source, and carrying out comprehensive evaluation on the monitoring well by combining the survey data with basic information of the monitoring well through a fuzzy comprehensive evaluation method;
s106, judging the monitoring performance of the monitoring wells according to the comprehensive evaluation of the monitoring wells and generating maintenance suggestions according to the monitoring performance of each monitoring well;
and S108, screening the monitoring wells according to whether the monitoring wells have the monitoring function or not based on the comprehensive evaluation result of the single monitoring well in the target area, and performing distribution optimization of the monitoring wells according to the distribution of the screened monitoring wells and the pollution source information.
The underground water resource monitoring well has the advantages that the number of monitoring indexes is large, the information amount is large, the monitoring precision is a key index for judging whether the monitoring well has a good monitoring function, the self-structure condition information of the monitoring well is one of important factors influencing the detection precision of underground water resources, a large amount of redundant information also exists in the self-structure condition of the monitoring well, and the monitoring function condition of the monitoring well is judged according to the determined evaluation index through the investigation of the self-structure condition of the monitoring well.
Fig. 2 shows a flowchart of a method of determining an evaluation index in the present invention.
According to the embodiment of the invention, the influence factors of the underground water environment monitoring precision of the monitoring well are obtained through big data retrieval, and the influence factors are as follows:
s202, setting keyword information through an underground water environment monitoring well and monitoring precision, retrieving relevant resource data through big data according to the keyword information, and selecting influence factors relevant to the state of the monitoring well through the relevant resource data to construct a knowledge graph;
s204, generating a nondirectional heterogeneous graph between monitoring precision of the monitoring well and influence factors according to the knowledge graph, and performing coding learning on the nondirectional heterogeneous graph through a graph convolution neural network;
s206, acquiring a low-dimensional vector of the monitoring precision and the influencing factors as an initial feature vector, and acquiring a final vector representation of the monitoring precision and the influencing factors through neighbor node aggregation and an attention mechanism;
s208, obtaining scores of the influence factors of the monitoring precision through vector inner products, generating a reverse ordering result according to the scores, selecting a preset number of influence factors according to the reverse ordering result, and obtaining survey data of the influence factors.
Wherein, a pair of nodes connected in the undirected heterogeneous graph
Will be
As initial feature vector, the node
And a node
The relationship between is expressed as
Wherein
Representing a weight matrix, representing nodes
To node
The contribution degree of (2) is Q represents a parameter matrix of feature transformation, a weight matrix is obtained through an attention mechanism, and the calculation mode is as follows:
wherein,
representing nodes
And node
The value of the attention force of (a),
it is shown that the activation function is,
representing vector mapping parameters, mapping vectors to real numbers,
representing the vector concatenation, the weight matrix is calculated in the manner of
Wherein k represents the number of terms of the influence factors, and N represents the total number of the influence factors;
node to be connected
The method is expressed by a neighbor node aggregation mechanism, and specifically comprises the following steps:
in the same wayGenerating a node
Vector representation of
After vector representation of monitoring precision and influence factors is generated through neighbor node aggregation and attention mechanism, the score of the monitoring precision on the influence factors is obtained by utilizing vector inner product
The method specifically comprises the following steps:
FIG. 3 shows a flow chart of a method for comprehensive evaluation of a monitoring well in the invention.
According to the embodiment of the invention, survey data is combined with basic information of a monitoring well to carry out comprehensive evaluation on the monitoring well through a fuzzy comprehensive evaluation method, which specifically comprises the following steps:
s302, determining an evaluation index according to the screened influence factors, and generating weight information of the evaluation index according to the scores of the influence factors;
s304, forming a factor set of fuzzy comprehensive evaluation according to the evaluation indexes, setting an evaluation set of monitoring well performance evaluation, obtaining the membership of each evaluation index to each element in the evaluation set through monitoring well basic information and survey data, and generating a membership matrix;
s306, acquiring a fuzzy comprehensive evaluation result according to the membership matrix and the weight information, and grading the monitoring wells according to the fuzzy comprehensive evaluation result of each monitoring well in the target area;
and S308, acquiring the scrapped monitoring wells in the target area according to the grading result, and marking according to the position information of the scrapped monitoring wells.
The evaluation index forming factor set is determined according to the influence factors, the evaluation set is formed according to the condition difference, the general condition and the excellent condition of the monitoring well, the triangular distribution function is adopted as the membership function, the survey data of the evaluation index is substituted into the membership calculation formula, the fuzzy evaluation matrix is obtained, the survey data of the evaluation index is obtained through the modes of an underground television, a micro-water test and the like, and the survey data of the evaluation index is formed through multi-source data.
It should be noted that, the monitoring performance of the monitoring wells is judged according to the comprehensive evaluation of the monitoring wells, and maintenance suggestions are generated according to the monitoring performance of each monitoring well, which specifically include: acquiring fuzzy comprehensive evaluation results of all monitoring wells in a target area and evaluation results of single evaluation indexes in the fuzzy comprehensive evaluation; acquiring the monitoring well of which the fuzzy comprehensive evaluation result is greater than a preset threshold value for judgment, selecting an evaluation index related to the monitoring performance of the monitoring well, presetting the threshold range and the grading standard of the related evaluation index, and judging whether the related evaluation index of the monitoring well in the target area is in the corresponding threshold range; if at least one evaluation index of the monitoring well is not in the corresponding threshold range, generating maintenance information of the monitoring well, and acquiring an unqualified evaluation index set of the monitoring well; acquiring the repair items of the monitoring well through the non-standard evaluation set, acquiring the scores of the repair items according to the threshold range of the evaluation indexes and the corresponding score standards, and judging the repairability of the repair items according to the scores; and screening repairable repair items according to the repairability, and generating maintenance suggestions through similar historical repair cases.
It should be noted that, the monitoring wells are screened according to whether the monitoring function is provided or not based on the comprehensive evaluation result of a single monitoring well in the target area, specifically: acquiring information of the scrapped monitoring wells according to the comprehensive evaluation result of the single monitoring well in the target area, and judging whether the number of the non-standard evaluation indexes in the non-standard evaluation index set of each monitoring well is larger than a preset number threshold value or not; judging the monitoring wells with the number of the scrapped monitoring wells or the monitoring wells with the number of the substandard evaluation indexes larger than a preset number threshold value as the monitoring wells without the monitoring function; according to the repairability of the monitoring well repairing project, representing the monitoring performance predicted value of the monitoring well within the preset time, and classifying the monitoring well with the monitoring performance predicted value smaller than the preset prediction threshold value as a monitoring well without the monitoring function; and marking the monitoring well without the monitoring function in the target area.
It should be noted that, the distribution optimization of the monitoring wells is performed according to the distribution of the screened monitoring wells and the pollution source information, specifically: removing the monitoring wells marked in the target area, acquiring pollution source information in the target area, and dividing the target area into a plurality of sub-areas according to the pollution source information; when the number information of the monitoring wells with the monitoring function in the sub-area is smaller than a preset threshold value, performing point distribution optimization on the monitoring wells; calculating mean square distance information between monitoring wells in the sub-area, and constructing a monitoring well optimization model based on a neural network of a genetic algorithm, wherein the neural network consists of an input layer, an output layer and a hidden layer, the hidden layer performs data calculation by arranging one or more layers of neurons, and each layer of neurons can be provided with a plurality of nodes; taking the mean square distance between monitoring wells as a fitness function; selecting candidate points of the newly added detection wells in the sub-area according to the hydrogeological information of the target area and the pollutant concentration information of the existing monitoring wells in the pollutant source position information sub-area, and optimally selecting the candidate points through the monitoring well optimization model according to the position information of the existing detection wells in the sub-area to determine the position information of the newly added monitoring wells.
According to the embodiment of the invention, the condition of pollutant migration in a target area is obtained according to the monitoring of the groundwater environment, and the method specifically comprises the following steps:
generating a groundwater flow field model according to hydrogeological information of a target area, and predicting pollutant migration through a convolutional neural network according to historical monitoring concentration change of pollutants in the target area;
acquiring a pollutant distribution range after preset time, and generating a range difference value between the pollutant distribution range after the preset time and the current pollutant distribution range;
when the range difference value is larger than a preset range difference threshold value, tracing the source of the pollutant according to the pollutant type information and the pollution source information in the target area, and maintaining the pollution source according to the tracing result;
meanwhile, a key treatment area is defined according to the distribution range of the pollutants and the concentration information of the pollutants monitored in the target area, and a retrieval label is established according to the types of the pollutants in the key treatment area and the hydrogeological information;
and acquiring related data with the similarity conforming to a preset range with the retrieval tag by a big data method, acquiring treatment schemes of other areas according to the related data, and formulating a groundwater environment treatment scheme of the key treatment area according to the enforceability.
The method comprises the steps of generating a groundwater flow field model through GMS three-dimensional groundwater migration software simulation, calculating water level lines such as aquifers of a target area, obtaining pollutant concentration of each monitoring well in a periodic detection process, generating time sequence change of a pollutant distribution range according to monitoring data of the monitoring wells, carrying out initialization training on a convolutional neural network according to the time sequence change of the pollutant distribution range, and predicting pollutant migration through the trained model.
FIG. 4 shows a block diagram of a comprehensive survey evaluation system for a monitoring well based on multi-source data.
The second aspect of the present invention also provides a monitoring well comprehensive survey evaluation system 4 based on multi-source data, which comprises: the monitoring well comprehensive investigation and evaluation method comprises a memory 41 and a processor 42, wherein the memory comprises a monitoring well comprehensive investigation and evaluation method program based on multi-source data, and when the monitoring well comprehensive investigation and evaluation method program based on the multi-source data is executed by the processor, the following steps are realized:
acquiring influence factors of underground water environment monitoring precision of the monitoring well through big data retrieval, screening the influence factors, and selecting a data source according to the screened influence factors;
acquiring survey data of the monitoring well according to the data source, and carrying out comprehensive evaluation on the monitoring well by combining the survey data with basic information of the monitoring well through a fuzzy comprehensive evaluation method;
judging the monitoring performance of the monitoring wells according to the comprehensive evaluation of the monitoring wells and generating maintenance suggestions according to the monitoring performance of each monitoring well;
and screening the monitoring wells according to whether the monitoring wells have the monitoring function or not based on the comprehensive evaluation result of the single monitoring well in the target area, and performing distribution optimization of the monitoring wells according to the distribution of the screened monitoring wells and the pollution source information.
The underground water resource monitoring well has the advantages that the number of monitoring indexes is large, the information amount is large, the monitoring precision is a key index for judging whether the monitoring well has a good monitoring function, the self-structure condition information of the monitoring well is one of important factors influencing the detection precision of underground water resources, a large amount of redundant information also exists in the self-structure condition of the monitoring well, and the monitoring function condition of the monitoring well is judged according to the determined evaluation index through the investigation of the self-structure condition of the monitoring well.
According to the embodiment of the invention, the influence factors of the underground water environment monitoring precision of the monitoring well are obtained through big data retrieval, and the influence factors are as follows:
setting keyword information through an underground water environment monitoring well and monitoring precision, obtaining related resource data through big data retrieval according to the keyword information, and selecting influence factors related to the state of the monitoring well through the related resource data to construct a knowledge graph;
generating a nondirectional heterogeneous graph between monitoring precision and influence factors of the monitoring well according to the knowledge graph, and performing coding learning on the nondirectional heterogeneous graph through a graph convolution neural network;
acquiring a low-dimensional vector of the monitoring precision and the influence factors as an initial feature vector, and acquiring a final vector representation of the monitoring precision and the influence factors through neighbor node aggregation and an attention mechanism;
obtaining scores of monitoring precision on the influence factors through vector inner products, generating a reverse ordering result according to the scores, selecting a preset number of influence factors according to the reverse ordering result, and obtaining investigation data of all the influence factors.
Wherein, a pair of nodes connected in the undirected heterogeneous graph
Will be
As initial feature vector, the node
And node
The relationship between is expressed as
Wherein
Representing a weight matrix, representing nodes
To node
The contribution degree of (2) is Q represents a parameter matrix of feature transformation, a weight matrix is obtained through an attention mechanism, and the calculation mode is as follows:
wherein,
representing nodes
And node
The value of the attention force of (a),
it is shown that the activation function is,
representing vector mapping parameters, mapping vectors to real numbers,
represents vector concatenation, thenThe weight matrix is calculated in the manner of
Wherein k represents the number of terms of the influence factors, and N represents the total number of the influence factors;
node to be connected
The method is expressed by a neighbor node aggregation mechanism, and specifically comprises the following steps:
in the same way, generating nodes
Vector representation of
After vector representation of monitoring precision and influence factors is generated through neighbor node aggregation and attention mechanism, the score of the monitoring precision on the influence factors is obtained by utilizing vector inner product
The method specifically comprises the following steps:
according to the embodiment of the invention, survey data is combined with basic information of a monitoring well to carry out comprehensive evaluation on the monitoring well through a fuzzy comprehensive evaluation method, which specifically comprises the following steps:
determining an evaluation index according to the screened influence factors, and generating weight information of the evaluation index according to the scores of the influence factors;
forming a factor set of fuzzy comprehensive evaluation according to the evaluation indexes, setting an evaluation set of monitoring well performance evaluation, obtaining the membership of each evaluation index to each element in the evaluation set through monitoring well basic information and survey data, and generating a membership matrix;
acquiring fuzzy comprehensive evaluation results according to the membership matrix and the weight information, and grading the monitoring wells according to the fuzzy comprehensive evaluation results of all the monitoring wells in the target area;
and acquiring the scrapped monitoring wells in the target area according to the grading result, and marking according to the position information of the scrapped monitoring wells.
The evaluation index forming factor set is determined according to the influence factors, the evaluation set is formed according to the condition difference, the general condition and the excellent condition of the monitoring well, the triangular distribution function is adopted as the membership function, the survey data of the evaluation index is substituted into the membership calculation formula, the fuzzy evaluation matrix is obtained, the survey data of the evaluation index is obtained through the modes of an underground television, a micro-water test and the like, and the survey data of the evaluation index is formed through multi-source data.
It should be noted that, the monitoring performance of the monitoring wells is judged according to the comprehensive evaluation of the monitoring wells, and maintenance suggestions are generated according to the monitoring performance of each monitoring well, which specifically include: acquiring fuzzy comprehensive evaluation results of all monitoring wells in a target area and evaluation results of single evaluation indexes in the fuzzy comprehensive evaluation; acquiring the monitoring well of which the fuzzy comprehensive evaluation result is greater than a preset threshold value for judgment, selecting an evaluation index related to the monitoring performance of the monitoring well, presetting the threshold range and the grading standard of the related evaluation index, and judging whether the related evaluation index of the monitoring well in the target area is in the corresponding threshold range; if at least one evaluation index of the monitoring well is not in the corresponding threshold range, generating monitoring well maintenance information, and acquiring a monitoring well non-standard evaluation index set; acquiring the repair items of the monitoring well through the non-standard evaluation set, acquiring the scores of the repair items according to the threshold range of the evaluation indexes and the corresponding score standards, and judging the repairability of the repair items according to the scores; and screening repairable repair items according to the repairability, and generating maintenance suggestions through similar historical repair cases.
It should be noted that, the monitoring wells are screened according to whether the monitoring function is provided or not based on the comprehensive evaluation result of a single monitoring well in the target area, specifically: acquiring information of the scrapped monitoring wells according to the comprehensive evaluation result of the single monitoring well in the target area, and judging whether the number of the non-standard evaluation indexes in the non-standard evaluation index set of each monitoring well is larger than a preset number threshold value or not; judging the monitoring wells with the number of the scrapped monitoring wells or the monitoring wells with the number of the substandard evaluation indexes larger than a preset number threshold value as the monitoring wells without the monitoring function; according to the repairability of the monitoring well repairing project, representing the monitoring performance predicted value of the monitoring well within the preset time, and classifying the monitoring well with the monitoring performance predicted value smaller than the preset prediction threshold value as a monitoring well without the monitoring function; and marking the monitoring wells without monitoring functions in the target area.
It should be noted that, the distribution optimization of the monitoring wells is performed by combining the distribution of the screened monitoring wells with the pollution source information, and specifically includes: removing the monitoring wells marked in the target area, acquiring pollution source information in the target area, and dividing the target area into a plurality of sub-areas according to the pollution source information; when the number information of the monitoring wells with the monitoring function in the sub-area is smaller than a preset threshold value, performing point distribution optimization on the monitoring wells; calculating mean square distance information between monitoring wells in the sub-area, and constructing a monitoring well optimization model based on a neural network of a genetic algorithm, wherein the neural network consists of an input layer, an output layer and a hidden layer, the hidden layer performs data calculation by arranging one or more layers of neurons, and each layer of neurons can be provided with a plurality of nodes; taking the mean square distance between monitoring wells as a fitness function; selecting candidate points of the newly added detection wells in the sub-area according to the hydrogeological information of the target area and the pollutant concentration information of the existing monitoring wells in the pollutant source position information sub-area, and optimally selecting the candidate points through the monitoring well optimization model according to the position information of the existing detection wells in the sub-area to determine the position information of the newly added monitoring wells.
The third aspect of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a program of a comprehensive survey evaluation method for a monitoring well based on multi-source data, and when the program of the comprehensive survey evaluation method for the monitoring well based on multi-source data is executed by a processor, the steps of the comprehensive survey evaluation method for the monitoring well based on multi-source data as described in any one of the above are implemented.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention or portions thereof contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
The above description is only for the specific 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 conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A monitoring well comprehensive investigation evaluation method based on multi-source data is characterized by comprising the following steps:
acquiring influence factors of underground water environment monitoring precision of the monitoring well through big data retrieval, screening the influence factors, and selecting a data source according to the screened influence factors;
acquiring survey data of the monitoring well according to the data source, and carrying out comprehensive evaluation on the monitoring well by combining the survey data with basic information of the monitoring well through a fuzzy comprehensive evaluation method;
judging the monitoring performance of the monitoring wells according to the comprehensive evaluation of the monitoring wells and generating maintenance suggestions according to the monitoring performance of each monitoring well;
and screening the monitoring wells according to whether the monitoring wells have the monitoring function or not based on the comprehensive evaluation result of the single monitoring well in the target area, and optimizing the distribution points of the monitoring wells according to the distribution of the screened monitoring wells and the pollution source information.
2. The comprehensive investigation and evaluation method for the monitoring well based on the multi-source data according to claim 1, characterized in that the influence factors of the underground water environment monitoring precision of the monitoring well are obtained through big data retrieval, and specifically:
setting keyword information through a groundwater environment monitoring well and monitoring precision, retrieving relevant resource data through big data according to the keyword information, and selecting influence factors relevant to the state of the monitoring well through the relevant resource data to construct a knowledge graph;
generating a nondirectional heterogeneous graph between monitoring precision and influence factors of the monitoring well according to the knowledge graph, and performing coding learning on the nondirectional heterogeneous graph through a graph convolution neural network;
acquiring a low-dimensional vector of the monitoring precision and the influence factors as an initial feature vector, and acquiring a final vector representation of the monitoring precision and the influence factors through neighbor node aggregation and an attention mechanism;
obtaining scores of monitoring precision on the influence factors through vector inner products, generating a reverse ordering result according to the scores, selecting a preset number of influence factors according to the reverse ordering result, and obtaining investigation data of all the influence factors.
3. The comprehensive survey evaluation method for the monitoring well based on the multi-source data, according to claim 1, is characterized in that the survey data is combined with basic information of the monitoring well to carry out comprehensive evaluation on the monitoring well by a fuzzy comprehensive evaluation method, and specifically comprises the following steps:
determining an evaluation index according to the screened influence factors, and generating weight information of the evaluation index according to the scores of the influence factors;
forming a factor set of fuzzy comprehensive evaluation according to the evaluation indexes, setting an evaluation set of monitoring well performance evaluation, obtaining the membership of each evaluation index to each element in the evaluation set through monitoring well basic information and survey data, and generating a membership matrix;
acquiring fuzzy comprehensive evaluation results according to the membership matrix and the weight information, and grading the monitoring wells according to the fuzzy comprehensive evaluation results of all the monitoring wells in the target area;
and acquiring the scrapped monitoring wells in the target area according to the grading result, and marking according to the position information of the scrapped monitoring wells.
4. The comprehensive investigation and evaluation method for the monitoring wells based on the multi-source data according to claim 1 is characterized in that the monitoring performance of the monitoring wells is judged according to the comprehensive evaluation of the monitoring wells, and maintenance suggestions are generated according to the monitoring performance of each monitoring well, and specifically the method comprises the following steps:
acquiring fuzzy comprehensive evaluation results of all monitoring wells in a target area and evaluation results of single evaluation indexes in the fuzzy comprehensive evaluation;
acquiring the monitoring well of which the fuzzy comprehensive evaluation result is greater than a preset threshold value for judgment, selecting an evaluation index related to the monitoring performance of the monitoring well, presetting the threshold range and the grading standard of the related evaluation index, and judging whether the related evaluation index of the monitoring well in the target area is in the corresponding threshold range;
if at least one evaluation index of the monitoring well is not in the corresponding threshold range, generating maintenance information of the monitoring well, and acquiring an unqualified evaluation index set of the monitoring well;
acquiring the repair items of the monitoring well through the non-standard evaluation set, acquiring the scores of the repair items according to the threshold range of the evaluation indexes and the corresponding score standards, and judging the repairability of the repair items according to the scores;
and screening repairable repair items according to the repairability, and generating maintenance suggestions through similar historical repair cases.
5. The comprehensive investigation and evaluation method for the monitoring wells based on the multi-source data as claimed in claim 1, wherein the monitoring wells are screened according to whether the monitoring function is available or not based on the comprehensive evaluation result of the single monitoring well in the target area, and specifically the method comprises the following steps:
acquiring information of the scrapped monitoring wells according to the comprehensive evaluation result of the single monitoring well in the target area, and judging whether the number of the non-standard evaluation indexes in the non-standard evaluation index set of each monitoring well is larger than a preset number threshold value or not;
judging the monitoring wells with the number of the scrapped monitoring wells or the monitoring wells with the number of the substandard evaluation indexes larger than a preset number threshold value as the monitoring wells without the monitoring function;
according to the repairability of the monitoring well repairing project, representing the monitoring performance predicted value of the monitoring well within the preset time, and classifying the monitoring well with the monitoring performance predicted value smaller than the preset prediction threshold value as a monitoring well without the monitoring function;
and marking the monitoring well without the monitoring function in the target area.
6. The comprehensive survey evaluation method for the monitoring wells based on the multi-source data, according to the claim 1, is characterized in that the distribution optimization of the monitoring wells is carried out according to the distribution of the screened monitoring wells and the pollution source information, and specifically comprises the following steps:
removing the monitoring wells marked in the target area, acquiring pollution source information in the target area, and dividing the target area into a plurality of sub-areas according to the pollution source information;
when the number information of the monitoring wells with the monitoring function in the sub-area is smaller than a preset threshold value, performing distribution optimization on the monitoring wells;
calculating the mean square distance information between monitoring wells in the sub-area, constructing a monitoring well optimization model based on a neural network of a genetic algorithm, and taking the mean square distance between the monitoring wells as a fitness function;
and generating position information of the newly added monitoring well through a monitoring well optimization model according to the hydrogeological information of the target area and the position information of the existing monitoring well in the sub-area.
7. A monitoring well comprehensive investigation evaluation system based on multi-source data is characterized by comprising: the monitoring well comprehensive investigation and evaluation method based on the multi-source data comprises a memory and a processor, wherein the memory comprises a monitoring well comprehensive investigation and evaluation method program based on the multi-source data, and the monitoring well comprehensive investigation and evaluation method program based on the multi-source data realizes the following steps when being executed by the processor:
acquiring influence factors of underground water environment monitoring precision of the monitoring well through big data retrieval, screening the influence factors, and selecting a data source according to the screened influence factors;
acquiring survey data of the monitoring well according to the data source, and carrying out comprehensive evaluation on the monitoring well by combining the survey data with basic information of the monitoring well through a fuzzy comprehensive evaluation method;
judging the monitoring performance of the monitoring wells according to the comprehensive evaluation of the monitoring wells and generating maintenance suggestions according to the monitoring performance of each monitoring well;
and screening the monitoring wells according to whether the monitoring wells have the monitoring function or not based on the comprehensive evaluation result of the single monitoring well in the target area, and performing distribution optimization of the monitoring wells according to the distribution of the screened monitoring wells and the pollution source information.
8. The comprehensive investigation and evaluation system for the monitoring well based on the multi-source data according to claim 7 is characterized in that the influence factors of the underground water environment monitoring precision of the monitoring well are obtained through big data retrieval, and specifically are as follows:
setting keyword information through an underground water environment monitoring well and monitoring precision, obtaining related resource data through big data retrieval according to the keyword information, and selecting influence factors related to the state of the monitoring well through the related resource data to construct a knowledge graph;
generating a nondirectional heterogeneous graph between monitoring precision and influence factors of the monitoring well according to the knowledge graph, and performing coding learning on the nondirectional heterogeneous graph through a graph convolution neural network;
acquiring a low-dimensional vector of monitoring precision and influence factors as an initial feature vector, and acquiring final vector representation of the monitoring precision and the influence factors through neighbor node aggregation and an attention mechanism;
obtaining scores of monitoring precision on the influence factors through vector inner products, generating a reverse ordering result according to the scores, selecting a preset number of influence factors according to the reverse ordering result, and obtaining investigation data of all the influence factors.
9. The comprehensive survey and evaluation system for the monitoring wells based on the multi-source data according to claim 7, characterized in that the monitoring performance of the monitoring wells is judged according to the comprehensive evaluation of the monitoring wells and maintenance suggestions are generated according to the monitoring performance of each monitoring well, specifically:
acquiring fuzzy comprehensive evaluation results of all monitoring wells in a target area and evaluation results of single evaluation indexes in the fuzzy comprehensive evaluation;
acquiring the monitoring well of which the fuzzy comprehensive evaluation result is greater than a preset threshold value for judgment, selecting an evaluation index related to the monitoring performance of the monitoring well, presetting the threshold range and the grading standard of the related evaluation index, and judging whether the related evaluation index of the monitoring well in the target area is in the corresponding threshold range;
if at least one evaluation index of the monitoring well is not in the corresponding threshold range, generating maintenance information of the monitoring well, and acquiring an unqualified evaluation index set of the monitoring well;
acquiring the repair items of the monitoring well through the non-standard evaluation set, acquiring the scores of the repair items according to the threshold range of the evaluation indexes and the corresponding score standards, and judging the repairability of the repair items according to the scores;
and screening repairable repair items according to the repairability, and generating maintenance suggestions through similar historical repair cases.
10. A computer-readable storage medium, wherein the computer-readable storage medium includes a program of a comprehensive survey evaluation method for monitoring wells based on multi-source data, and when the program of the comprehensive survey evaluation method for monitoring wells based on multi-source data is executed by a processor, the steps of the comprehensive survey evaluation method for monitoring wells based on multi-source data according to any one of claims 1 to 6 are implemented.
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