Regional environment bearing capacity monitoring system based on hydrogeological parameters

Abstract

The invention discloses a regional environment bearing capacity monitoring system based on hydrogeological parameters, and relates to the technical field of monitoring management. Historical ecological data of water resources in a region with the hydrogeological parameters are collected, and the collected historical ecological data of the water resources are processed; and analyzing the obtained processed historical ecological data of the water resource through a data analysis method, constructing an environmental bearing capacity evaluation index system based on the obtained analyzed historical ecological data of the water resource, and constructing an environmental bearing capacity evaluation model through an iterative calculation mode based on the obtained environmental bearing capacity evaluation index system. The method comprises the following steps: determining the hydrogeological parameters, simultaneously performing optimization, performing real-time prediction and monitoring to determine the environmental bearing capacity score in the region of the hydrogeological parameters through a prediction analysis method and a real-time processing mode after the optimization is completed, finally comparing a prediction result with a monitoring determination result, and performing real-time monitoring management based on a comparison result.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring and management, and in particular to a regional environmental carrying capacity monitoring system based on hydrogeological parameters. Background Art

[0002] Since the water environment carrying capacity and social living standards in various regions of my country are not the same, the unreasonable regional environmental carrying capacity monitoring layout of hydrogeological parameters makes it difficult to balance the relationship between water environment carrying capacity and intelligent monitoring and management of environmental carrying capacity, and cannot play an important role in protecting the water environment and promoting social and economic development.

[0003] Existing technology, such as the invention patent application with publication number CN113487174A, discloses a water environment carrying capacity assessment, early warning and control method, which includes: dividing the water environment into environmental carrying states and corresponding early warning levels by setting three assessment indicators of water environment, water ecology and water resources, establishing a water environment carrying capacity assessment pre-model, evaluating the assessment indicator data and corresponding early warning levels for a future preset time period, and regulating the assessment indicators with high early warning levels for the future preset time period.

[0004] From the above scheme, it can be seen that the current regional environmental carrying capacity monitoring cycle of hydrogeological parameters is long, resulting in insufficient data accuracy. The accuracy of the bearing capacity prediction for the preset time period in the future is not high, which is insufficient to meet actual needs. Summary of the Invention

[0005] The purpose of the present invention is to provide a regional environmental carrying capacity monitoring system based on hydrogeological parameters, which solves the problem in the background technology that it is difficult to balance the relationship between water environmental carrying capacity and intelligent monitoring and management of environmental carrying capacity.

[0006] In order to solve the above-mentioned technical problem of difficulty in balancing the relationship between water environment carrying capacity and intelligent monitoring and management of environmental carrying capacity, the present invention adopts the following technical solution: The present invention provides a regional environmental carrying capacity monitoring system based on hydrogeological parameters, which specifically includes the following steps:

[0007] S1. Collecting historical water resource ecological data within the area of ​​hydrogeological parameters, and processing the collected historical water resource ecological data to obtain processed historical water resource ecological data;

[0008] S2. Analyzing the processed historical water resource ecological data using a data analysis method to obtain analyzed historical water resource ecological data, and constructing an environmental carrying capacity evaluation index system based on the analyzed historical water resource ecological data;

[0009] S21. Analyze the processed historical water resource ecological data using data analysis methods and select environmental carrying capacity evaluation indicators;

[0010] S22. Determine the indicator weight corresponding to the selected environmental carrying capacity evaluation indicator;

[0011] S23. Construct an environmental carrying capacity evaluation index system based on the indicator weights of the environmental carrying capacity evaluation indicators;

[0012] S3. Based on the obtained environmental carrying capacity evaluation index system, an environmental carrying capacity evaluation model is constructed through iterative calculation, and the environmental carrying capacity evaluation model is optimized through deep learning to obtain an optimized environmental carrying capacity evaluation model;

[0013] S4. Summarize and analyze the historical ecological data of water resources and the optimized environmental carrying capacity evaluation model, and use the prediction analysis method to predict the environmental carrying capacity score of the region with hydrogeological parameters in real time;

[0014] S5. Collect water resource ecological data in the area of ​​the hydrogeological parameters in real time, and input the collected water resource ecological data into the optimized environmental carrying capacity evaluation model to determine the environmental carrying capacity score in the area of ​​the current hydrogeological parameters in real time;

[0015] S6. Compare the environmental carrying capacity score in the area where the hydrogeological parameters are predicted in real time with the environmental carrying capacity score in the area where the current hydrogeological parameters are determined in real time, and conduct real-time monitoring and management based on the comparison results.

[0016] Preferably, the collecting of historical water resource ecological data in the area of ​​hydrogeological parameters and processing the collected historical water resource ecological data to obtain the processed historical water resource ecological data comprises the following steps:

[0017] S11. Filtering the collected historical ecological data of water resources;

[0018] S12, constructing a sample set using the aggregated and processed historical water resource ecological data;

[0019] Construct sample set N={N1,N2,...,N n};

[0020] Among them, N represents the sample set, N1 represents the first set of processed water resources historical ecological data in the sample set, and N n The nth group of processed historical water resources ecological data in the sample set.

[0021] Preferably, filtering the collected historical water resource ecological data comprises the following steps:

[0022] Processing the collected historical water resource ecological data through binary processing, and outputting binary-converted historical water resource ecological data;

[0023] Create an array of length l and select A hash function is used to calculate the transformed historical ecological data of water resources and the calculation results are stored in an array;

[0024] Among them, R represents the number of hash functions, and z represents the amount of water resources historical ecological data after transformation;

[0025] During the process of calculating the transformed water resources historical ecological data using the hash function, when the calculation results of two sets of transformed water resources historical ecological data are consistent, the two sets of transformed water resources historical ecological data are set as duplicate data;

[0026] When two sets of transformed water resources historical ecological data are duplicate data, one set of transformed water resources historical ecological data is deleted to achieve filtering processing;

[0027] After the calculation is completed, the converted water resources historical ecological data stored in the array during the calculation process are summarized to obtain the processed water resources historical ecological data.

[0028] Preferably, determining the indicator weight corresponding to the selected environmental carrying capacity evaluation indicator includes the following steps:

[0029] Determine the weight of the corresponding selected environmental carrying capacity evaluation index through the entropy method;

[0030] S221. Calculate the positive and negative indicators in the selected environmental carrying capacity evaluation indicators;

[0031] Process and update the selected environmental carrying capacity evaluation indicators according to the positive indicator calculation formula and the negative indicator calculation formula;

[0032]

[0033] in, It represents the score of the jth positive indicator in the mth environmental carrying capacity evaluation index, A represents the score of the jth negative indicator in the mth environmental carrying capacity evaluation index. mj It represents the score of the jth indicator in the mth environmental carrying capacity evaluation index after treatment;

[0034] S222. Calculate the weight of the indicator based on the calculated positive indicator and negative indicator;

[0035]

[0036] Among them, P mj is the weight value of the jth indicator in the mth environmental carrying capacity evaluation index, and J represents the number of indicators;

[0037] S223. Calculate the entropy value of the corresponding indicator;

[0038] Calculate the entropy value u of the j-th indicator j , the formula is:

[0039]

[0040] S224. Calculate the utility value of the corresponding indicator;

[0041] Calculate the utility value g of the j-th indicator information j , the formula is: g j =1-u j ;

[0042] S225. Calculate the entropy weight of the corresponding indicator;

[0043] The calculation formula for each indicator weight is as follows:

[0044]

[0045] Among them, W j is the indicator weight of the j-th indicator.

[0046] Preferably, the step of constructing an environmental carrying capacity evaluation index system based on determining the index weights of the environmental carrying capacity evaluation indexes comprises the following steps:

[0047] Summarize and determine the indicator weights of environmental carrying capacity evaluation indicators and evenly divide the indicator weights of environmental carrying capacity evaluation indicators into three parts: the highest level, the middle level and the lowest level according to the indicator weight order;

[0048] Compare the weights of indicators in the same part in pairs and build a comparison matrix based on the comparison results;

[0049] The calculation formula for the comparison result is as follows:

[0050]

[0051] Among them, W jk Indicates the indicator weight W j and indicator weight W k The comparison results, ω jk The comparison grade value of the comparison matrix represents the score of the corresponding indicator;

[0052] Set a selection threshold for the comparison level value, determine the indicators corresponding to the three parts based on the set selection threshold, and record the scores of the corresponding indicators;

[0053] The indicators corresponding to the three parts are summarized and determined to construct an environmental carrying capacity evaluation index system.

[0054] Preferably, the environmental carrying capacity evaluation model is constructed by iterative calculation based on the obtained environmental carrying capacity evaluation index system, and the environmental carrying capacity evaluation model is optimized by deep learning to obtain the optimized environmental carrying capacity evaluation model, which includes the following steps:

[0055] S31. Construct an environmental carrying capacity assessment model through iterative calculation;

[0056] S32. Based on the constructed environmental carrying capacity assessment model, set the genetic population size, number of iterations, and chromosome encoding;

[0057] Each population is set as a set of analyzed historical ecological data of water resources;

[0058] S33. Randomly select b water resources historical ecological data in each category to generate the initial population S gen ;

[0059] S34. Use the constructed environmental carrying capacity evaluation model as the fitness function and calculate the fitness of each individual in the population;

[0060] Assume that each individual represents a set of environmental carrying capacity evaluation index system data;

[0061] The formula for calculating individual fitness is as follows:

[0062]

[0063] Among them, Fit(t) represents the fitness of the t-th individual, and ε represents the environmental carrying capacity evaluation model;

[0064] S35. Select the best individuals from all individuals based on the roulette wheel method;

[0065] The calculation formula for selecting the best individual among all individuals in the roulette wheel method is as follows:

[0066]

[0067] Among them, p(t) represents the probability of individual t being selected, and T represents the population size;

[0068] S36, based on the chromosome coding of the selected excellent individuals, cross the selected excellent individuals in a sequential crossover manner, and set the new population generated after the crossover to be S' gen ;

[0069] S37. Randomly select an individual from the population and mutate it with a set probability. Set the population after the mutation to S” gen ;

[0070] S38, comparing the fitness difference ΔFit between the initial population and the population after crossover mutation using the genetic algorithm;

[0071] When ΔFit < 0, it means that the fitness of the mutated population is higher than that of the initial population, and the population is accepted. When ΔFit ≥ 0, it means that the fitness of the mutated population is lower than that of the initial population, and the population is rejected.

[0072] S39, judging whether the maximum number of iterations has been reached according to the number of iterations of the algorithm, outputting the optimal solution if the maximum number of iterations has been reached, and continuing to execute step S35 if the maximum number of iterations has not been reached;

[0073] The optimal solution output is set as the optimized environmental carrying capacity assessment model.

[0074] Preferably, the construction of the environmental carrying capacity assessment model by iterative calculation comprises the following steps:

[0075] The environmental carrying capacity evaluation model is set to consist of various environmental carrying capacity evaluation indicators;

[0076] The calculation formula of the environmental carrying capacity assessment model is as follows:

[0077]

[0078] Among them, WB y (v′1,y,v' 2,y ,...,v' m,y ) is the constructed environmental carrying capacity evaluation model, which represents the environmental carrying capacity evaluation results of various indicators in year y, v' m,y represents the mean value of the mth indicator in the yth year, W j ,W k Represents the indicator weights of the jth and kth indicators, v' jy represents the standard value of the jth indicator in the yth year, v' ky It represents the standard value of the kth indicator in the yth year.

[0079] Preferably, the summarized and analyzed historical water resource ecological data and the optimized environmental carrying capacity evaluation model are used to predict the environmental carrying capacity score in the region of hydrogeological parameters in real time through a prediction analysis method, including the following steps:

[0080] Construct the original time series X (0) =[X (0) 1,X (0) 2,...,X (0) d];

[0081] Among them, X (0) d represents the d-th original time series;

[0082] The environmental carrying capacity scoring formula for the area of ​​real-time prediction of hydrogeological parameters is as follows:

[0083]

[0084]

[0085] in, is the autoregressive coefficient polynomial of the historical ecological data of water resources after analysis, θ q (L) is the sliding mean coefficient polynomial of the environmental carrying capacity assessment model, L represents the lag operator, θ q represents the coefficient weight of the qth time series, λ (0) represents a white noise sequence, (1-L) θ The lag operator L represents the θ-order difference of the sequence, Y q represents the environmental carrying capacity score of the qth time series forecast.

[0086] Preferably, the comparing of the environmental carrying capacity scores within the region where the hydrogeological parameters are predicted in real time and the determining of the environmental carrying capacity scores within the region where the current hydrogeological parameters are determined in real time, and the real-time monitoring and management based on the comparison results include the following steps:

[0087] Setting a threshold for comparing the environmental carrying capacity score within the region where the hydrogeological parameters are predicted in real time with the environmental carrying capacity score within the region where the current hydrogeological parameters are determined in real time;

[0088] When the difference between the environmental carrying capacity score in the area where the hydrogeological parameters are predicted in real time and the environmental carrying capacity score in the area where the current hydrogeological parameters are determined in real time is greater than the set comparison result threshold, the collection cycle of water resource ecological data in the area where the hydrogeological parameters are predicted in real time is shortened.

[0089] The present invention also discloses a regional environmental carrying capacity monitoring system based on hydrogeological parameters, comprising: a data acquisition module, a data processing module, a data analysis module, an evaluation model building module, a prediction module and a comparison management module;

[0090] The data acquisition module is used to collect water resource ecological data within the area of ​​hydrogeological parameters;

[0091] The data processing module is used to process the collected water resources ecological data;

[0092] The data analysis module is used to analyze the processed water resource ecological data;

[0093] The evaluation model building module is used to build and determine the evaluation model according to the analysis results;

[0094] The prediction module is used to make real-time predictions based on the analyzed water resource ecological data and the determined evaluation model;

[0095] The comparison management module is used to compare the predicted data and the real-time monitoring data, and to adjust the monitoring management cycle of the region of hydrogeological parameters.

[0096] The beneficial effects of the present invention are:

[0097] (1) The present invention collects historical ecological data of water resources in the area of ​​hydrogeological parameters, processes the collected historical ecological data of water resources, and analyzes the processed historical ecological data of water resources through a data analysis method. At the same time, an environmental carrying capacity evaluation index system is constructed based on the analyzed historical ecological data of water resources, and an environmental carrying capacity evaluation model is constructed through an iterative calculation method based on the obtained environmental carrying capacity evaluation index system, and optimization is performed at the same time. After the optimization is completed, the environmental carrying capacity score of the area of ​​hydrogeological parameters is predicted and monitored in real time through a prediction analysis method and a real-time processing method. Finally, the prediction result and the monitoring result are compared, and real-time monitoring and management are performed based on the comparison result.

[0098] (2) The present invention improves the reliability of the water resources historical ecological data by filtering the collected water resources historical ecological data, traversing the collected water resources historical ecological data through binary processing and dynamically setting a hash function, and comparing and filtering the traversal results.

[0099] (3) The present invention analyzes the processed historical ecological data of water resources by using a data analysis method, and selects environmental carrying capacity evaluation indicators through expert scoring. After the selection is completed, the indicator weights of the corresponding selected environmental carrying capacity evaluation indicators are determined by the entropy weight method. Finally, an environmental carrying capacity evaluation indicator system is constructed based on the indicator weights of the determined environmental carrying capacity evaluation indicators, thereby improving the accuracy of environmental carrying capacity evaluation.

[0100] (4) The present invention constructs an environmental carrying capacity evaluation model through iterative calculation. After the environmental carrying capacity evaluation model is constructed, the optimal environmental carrying capacity evaluation model is dynamically determined through fitness analysis, crossover, and mutation iteration through a genetic algorithm, thereby improving the stability of the environmental carrying capacity evaluation model.

[0101] (5) The present invention improves the accuracy of environmental carrying capacity score prediction by summarizing and analyzing historical water resource ecological data and the optimized environmental carrying capacity evaluation model, and by recording time series data and predictive analysis methods to predict the environmental carrying capacity score in the region of hydrogeological parameters in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0102] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0103] Figure 1 It is a flow chart of the method for monitoring the regional environmental carrying capacity of hydrogeological parameters of the present invention. DETAILED DESCRIPTION

[0104] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0105] In a specific embodiment of the present invention,

[0106] Reference Figure 1 As shown, the present invention provides a regional environmental carrying capacity monitoring system based on hydrogeological parameters, comprising the following steps:

[0107] S1. Collecting historical water resource ecological data within the area of ​​hydrogeological parameters, and processing the collected historical water resource ecological data to obtain processed historical water resource ecological data;

[0108] S2. Analyzing the processed historical water resource ecological data using a data analysis method to obtain analyzed historical water resource ecological data, and constructing an environmental carrying capacity evaluation index system based on the analyzed historical water resource ecological data;

[0109] S21. Analyze the processed historical water resource ecological data using data analysis methods and select environmental carrying capacity evaluation indicators;

[0110] S22. Determine the indicator weight corresponding to the selected environmental carrying capacity evaluation indicator;

[0111] S23. Construct an environmental carrying capacity evaluation index system based on the indicator weights of the environmental carrying capacity evaluation indicators;

[0112] S3. Based on the obtained environmental carrying capacity evaluation index system, an environmental carrying capacity evaluation model is constructed through iterative calculation, and the environmental carrying capacity evaluation model is optimized through deep learning to obtain an optimized environmental carrying capacity evaluation model;

[0113] S4. Summarize and analyze the historical ecological data of water resources and the optimized environmental carrying capacity evaluation model, and use the prediction analysis method to predict the environmental carrying capacity score of the region with hydrogeological parameters in real time;

[0114] S5. Collect water resource ecological data in the area of ​​the hydrogeological parameters in real time, and input the collected water resource ecological data into the optimized environmental carrying capacity evaluation model to determine the environmental carrying capacity score in the area of ​​the current hydrogeological parameters in real time;

[0115] S6. Compare the environmental carrying capacity score in the area where the hydrogeological parameters are predicted in real time with the environmental carrying capacity score in the area where the current hydrogeological parameters are determined in real time, and conduct real-time monitoring and management based on the comparison results.

[0116] Further, refer to Figure 1 As shown, collecting historical water resource ecological data in the area of ​​hydrogeological parameters and processing the collected historical water resource ecological data to obtain the processed historical water resource ecological data includes the following steps:

[0117] S11. Filtering the collected historical ecological data of water resources;

[0118] Processing the collected historical water resource ecological data through binary processing, and outputting binary-converted historical water resource ecological data;

[0119] Furthermore, create an array of length l and select A hash function is used to calculate the transformed historical ecological data of water resources and the calculation results are stored in an array;

[0120] Among them, R represents the number of hash functions, and z represents the amount of water resources historical ecological data after transformation;

[0121] During the process of calculating the transformed water resources historical ecological data using the hash function, when the calculation results of two sets of transformed water resources historical ecological data are consistent, the two sets of transformed water resources historical ecological data are set as duplicate data;

[0122] When two sets of transformed water resources historical ecological data are duplicate data, one set of transformed water resources historical ecological data is deleted to achieve filtering processing;

[0123] After the calculation is completed, the transformed water resource historical ecological data stored in the array during the calculation process is summarized to obtain the processed water resource historical ecological data;

[0124] S12, constructing a sample set using the aggregated and processed historical water resource ecological data;

[0125] Construct sample set N={N1,N2,...,N n};

[0126] Among them, N represents the sample set, N1 represents the first set of processed water resources historical ecological data in the sample set, and N n The nth group of processed historical ecological data of water resources in the sample set;

[0127] Further, refer to Figure 1 As shown, the processed historical water resource ecological data is analyzed by data analysis methods, and the selection of environmental carrying capacity evaluation indicators includes the following steps:

[0128] The processed historical ecological data of water resources include 14 evaluation indicators, including total water consumption, sewage discharge, annual precipitation, green coverage rate, and water resource development and utilization rate;

[0129] Collect the scoring data of 14 evaluation indicators from different experts based on their own experience, and calculate the subjective scoring data of each evaluation indicator;

[0130] The formula for calculating subjective scoring data is as follows:

[0131]

[0132] in, Represents the calculated subjective scoring data of each evaluation indicator, μ i represents the scoring data of the i-th expert, and I represents the number of experts;

[0133] Set a subjective scoring data threshold for the evaluation indicators and remove the evaluation indicators whose subjective scoring data is lower than the set subjective scoring data threshold;

[0134] Further, refer to Figure 1 As shown, determining the indicator weight corresponding to the selected environmental carrying capacity evaluation indicator includes the following steps:

[0135] Determine the weight of the corresponding selected environmental carrying capacity evaluation index through the entropy method;

[0136] S221. Calculate the positive and negative indicators in the selected environmental carrying capacity evaluation indicators;

[0137] Process and update the selected environmental carrying capacity evaluation indicators according to the positive indicator calculation formula and the negative indicator calculation formula;

[0138]

[0139] in, It represents the score of the jth positive indicator in the mth environmental carrying capacity evaluation index, A represents the score of the jth negative indicator in the mth environmental carrying capacity evaluation index. mj It represents the score of the jth indicator in the mth environmental carrying capacity evaluation index after treatment;

[0140] S222. Calculate the weight of the indicator based on the calculated positive indicator and negative indicator;

[0141]

[0142] Among them, P mj is the weight value of the jth indicator in the mth environmental carrying capacity evaluation index, and J represents the number of indicators;

[0143] S223. Calculate the entropy value of the corresponding indicator;

[0144] Calculate the entropy value u of the j-th indicator j , the formula is:

[0145]

[0146] S224. Calculate the utility value of the corresponding indicator;

[0147] Calculate the utility value g of the j-th indicator information j , the formula is: g j =1-u j ;

[0148] S225. Calculate the entropy weight of the corresponding indicator;

[0149] The calculation formula for each indicator weight is as follows:

[0150]

[0151] Among them, W j is the indicator weight of the j-th indicator;

[0152] Further, refer to Figure 1 As shown in FIG, constructing an environmental carrying capacity evaluation index system based on determining the index weights of environmental carrying capacity evaluation indicators includes the following steps:

[0153] Summarize and determine the indicator weights of environmental carrying capacity evaluation indicators and evenly divide the indicator weights of environmental carrying capacity evaluation indicators into three parts: the highest level, the middle level and the lowest level according to the indicator weight order;

[0154] Furthermore, the weights of indicators in the same part are compared pairwise, and a comparison matrix is ​​constructed based on the comparison results;

[0155] The calculation formula for the comparison result is as follows:

[0156]

[0157] Among them, W jk Indicates the indicator weight W j and indicator weight W k The comparison results, ω jk The comparison grade value of the comparison matrix represents the score of the corresponding indicator;

[0158] Set a selection threshold for the comparison level value, determine the indicators corresponding to the three parts based on the set selection threshold, and record the scores of the corresponding indicators;

[0159] Furthermore, the indicators corresponding to the three parts are summarized and determined to construct an environmental carrying capacity evaluation index system;

[0160] Further, refer to Figure 1 As shown in FIG, based on the obtained environmental carrying capacity evaluation index system, an environmental carrying capacity evaluation model is constructed through iterative calculation, and the environmental carrying capacity evaluation model is optimized through deep learning. The optimized environmental carrying capacity evaluation model includes the following steps:

[0161] S31. Construct an environmental carrying capacity assessment model through iterative calculation;

[0162] The environmental carrying capacity evaluation model is set to consist of various environmental carrying capacity evaluation indicators;

[0163] The calculation formula of the environmental carrying capacity assessment model is as follows:

[0164]

[0165] Among them, WB y (v′1,y,v' 2,y ,...,v' m,y ) is the constructed environmental carrying capacity evaluation model, which represents the environmental carrying capacity evaluation results of various indicators in year y, v' m,y represents the mean value of the mth indicator in the yth year, W j ,W k Represents the indicator weights of the jth and kth indicators, v' jy represents the standard value of the jth indicator in the yth year, v' ky represents the standard value of the kth indicator in the yth year;

[0166] S32. Based on the constructed environmental carrying capacity assessment model, set the genetic population size, number of iterations, and chromosome encoding;

[0167] Each population is set as a set of analyzed historical ecological data of water resources;

[0168] S33. Randomly select b water resources historical ecological data in each category to generate the initial population Sgen ;

[0169] S34. Use the constructed environmental carrying capacity evaluation model as the fitness function and calculate the fitness of each individual in the population;

[0170] Assume that each individual represents a set of environmental carrying capacity evaluation index system data;

[0171] The formula for calculating the fitness of an individual is as follows:

[0172]

[0173] Among them, Fit(t) represents the fitness of the t-th individual, and ε represents the environmental carrying capacity evaluation model;

[0174] S35. Select the best individuals from all individuals based on the roulette wheel method;

[0175] The calculation formula for selecting the best individual among all individuals in the roulette wheel method is as follows:

[0176]

[0177] Among them, p(t) represents the probability of individual t being selected, and T represents the population size;

[0178] S36, based on the chromosome coding of the selected excellent individuals, cross the selected excellent individuals in a sequential crossover manner, and set the new population generated after the crossover to be S' gen ;

[0179] S37. Randomly select an individual from the population and mutate it with a set probability. Set the population after the mutation to S” gen ;

[0180] S38, comparing the fitness difference ΔFit between the initial population and the population after crossover mutation using the genetic algorithm;

[0181] When ΔFit < 0, it means that the fitness of the mutated population is higher than that of the initial population, and the population is accepted. When ΔFit ≥ 0, it means that the fitness of the mutated population is lower than that of the initial population, and the population is rejected.

[0182] S39, judging whether the maximum number of iterations has been reached according to the number of iterations of the algorithm, outputting the optimal solution if the maximum number of iterations has been reached, and continuing to execute step S35 if the maximum number of iterations has not been reached;

[0183] The optimal solution output is set as the optimized environmental carrying capacity assessment model;

[0184] Further, refer to Figure 1As shown in the figure, the historical ecological data of water resources after summary analysis and the optimized environmental carrying capacity evaluation model are used to predict the environmental carrying capacity score of the area with hydrogeological parameters in real time through the prediction analysis method, including the following steps:

[0185] Construct the original time series X (0) =[X (0) 1,X (0) 2,...,X (0) d];

[0186] Among them, X (0) d represents the d-th original time series;

[0187] The environmental carrying capacity scoring formula for the area of ​​real-time prediction of hydrogeological parameters is as follows:

[0188]

[0189]

[0190] in, is the autoregressive coefficient polynomial of the historical ecological data of water resources after analysis, θ q (L) is the sliding mean coefficient polynomial of the environmental carrying capacity assessment model, L represents the lag operator, θ q represents the coefficient weight of the qth time series, λ (0) represents a white noise sequence, (1-L) θ The lag operator L represents the θ-order difference of the sequence, Y q represents the environmental carrying capacity score of the qth time series forecast;

[0191] Further, refer to Figure 1 As shown, comparing the environmental carrying capacity score in the area where the real-time prediction of hydrogeological parameters is made and the environmental carrying capacity score in the area where the current hydrogeological parameters are determined in real time, and real-time monitoring and management based on the comparison results include the following steps:

[0192] Setting a threshold for comparing the environmental carrying capacity score within the region where the hydrogeological parameters are predicted in real time with the environmental carrying capacity score within the region where the current hydrogeological parameters are determined in real time;

[0193] When the difference between the environmental carrying capacity score in the area where the hydrogeological parameters are predicted in real time and the environmental carrying capacity score in the area where the current hydrogeological parameters are determined in real time is greater than a set comparison result threshold, the collection period of water resource ecological data in the area where the hydrogeological parameters are predicted in real time is shortened;

[0194] In a specific embodiment, the regional environmental carrying capacity monitoring system based on hydrogeological parameters includes: a data acquisition module, a data processing module, a data analysis module, an evaluation model construction module, a prediction module and a comparison management module;

[0195] The data acquisition module is used to collect water resource ecological data within the area of ​​hydrogeological parameters;

[0196] The data processing module is used to process the collected water resources ecological data;

[0197] The data analysis module is used to analyze the processed water resource ecological data;

[0198] The evaluation model building module is used to build and determine the evaluation model according to the analysis results;

[0199] The prediction module is used to make real-time predictions based on the analyzed water resource ecological data and the determined evaluation model;

[0200] The comparison management module is used to compare the predicted data and the real-time monitoring data, and to adjust the monitoring management cycle of the region of hydrogeological parameters.

[0201] It should be noted that the above content is merely an example and explanation of the concept of the present invention. Technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the scope of protection of the present invention.

Claims

1. A regional environmental carrying capacity monitoring system based on hydrogeological parameters, characterized in that: The following steps are involved: S1. Collecting historical water resource ecological data within the area of ​​hydrogeological parameters, and processing the collected historical water resource ecological data to obtain processed historical water resource ecological data; S2. Analyzing the processed historical water resource ecological data using a data analysis method to obtain analyzed historical water resource ecological data, and constructing an environmental carrying capacity evaluation index system based on the analyzed historical water resource ecological data; S21. Analyze the processed historical water resource ecological data using data analysis methods and select environmental carrying capacity evaluation indicators; S22. Determine the indicator weight corresponding to the selected environmental carrying capacity evaluation indicator; S23. Construct an environmental carrying capacity evaluation index system based on the indicator weights of the environmental carrying capacity evaluation indicators; S3. Based on the obtained environmental carrying capacity evaluation index system, an environmental carrying capacity evaluation model is constructed through iterative calculation, and the environmental carrying capacity evaluation model is optimized through deep learning to obtain an optimized environmental carrying capacity evaluation model; S4. Summarize and analyze the historical ecological data of water resources and the optimized environmental carrying capacity evaluation model, and use the prediction analysis method to predict the environmental carrying capacity score of the region with hydrogeological parameters in real time; S5. Collect water resource ecological data in the area of ​​the hydrogeological parameters in real time, and input the collected water resource ecological data into the optimized environmental carrying capacity evaluation model to determine the environmental carrying capacity score in the area of ​​the current hydrogeological parameters in real time; S6. Compare the environmental carrying capacity score in the area where the hydrogeological parameters are predicted in real time with the environmental carrying capacity score in the area where the current hydrogeological parameters are determined in real time, and conduct real-time monitoring and management based on the comparison results.

2. A regional environmental carrying capacity monitoring system based on hydrogeological parameters according to claim 1, characterized in that: The collecting of historical water resource ecological data in the area of ​​hydrogeological parameters and processing the collected historical water resource ecological data to obtain the processed historical water resource ecological data comprises the following steps: S11. Filtering the collected historical ecological data of water resources; S12, constructing a sample set using the aggregated and processed historical water resource ecological data; Construct sample set N={N1,N2,...,N n }; Among them, N represents the sample set, N1 represents the first set of processed water resources historical ecological data in the sample set, and N n The nth group of processed historical water resources ecological data in the sample set.

3. A regional environmental carrying capacity monitoring system based on hydrogeological parameters according to claim 2, characterized in that: The filtering of the collected water resources historical ecological data includes the following steps: Processing the collected historical water resource ecological data through binary processing, and outputting binary-converted historical water resource ecological data; Create an array of length l and select A hash function is used to calculate the transformed historical ecological data of water resources and the calculation results are stored in an array; Among them, R represents the number of hash functions, and z represents the amount of water resources historical ecological data after transformation; During the process of calculating the transformed water resources historical ecological data using the hash function, when the calculation results of two sets of transformed water resources historical ecological data are consistent, the two sets of transformed water resources historical ecological data are set as duplicate data; When two sets of transformed water resources historical ecological data are duplicate data, one set of transformed water resources historical ecological data is deleted to achieve filtering processing; After the calculation is completed, the converted water resources historical ecological data stored in the array during the calculation process are summarized to obtain the processed water resources historical ecological data.

4. A regional environmental carrying capacity monitoring system based on hydrogeological parameters according to claim 1, characterized in that: Determining the indicator weight corresponding to the selected environmental carrying capacity evaluation indicator includes the following steps: Determine the weight of the corresponding selected environmental carrying capacity evaluation index through the entropy method; S221. Calculate the positive and negative indicators in the selected environmental carrying capacity evaluation indicators; Process and update the selected environmental carrying capacity evaluation indicators according to the positive indicator calculation formula and the negative indicator calculation formula; in, It represents the score of the jth positive indicator in the mth environmental carrying capacity evaluation index, A represents the score of the jth negative indicator in the mth environmental carrying capacity evaluation index. mj It represents the score of the jth indicator in the mth environmental carrying capacity evaluation index after treatment; S222. Calculate the weight of the indicator based on the calculated positive indicator and negative indicator; Among them, P mj is the weight value of the jth indicator in the mth environmental carrying capacity evaluation index, and J represents the number of indicators; S223. Calculate the entropy value of the corresponding indicator; Calculate the entropy value u of the j-th indicator j , the formula is: S224. Calculate the utility value of the corresponding indicator; Calculate the utility value g of the j-th indicator information j , the formula is: g j =1-u j ; S225. Calculate the entropy weight of the corresponding indicator; The calculation formula for each indicator weight is as follows: Among them, W j is the indicator weight of the j-th indicator.

5. The regional environmental carrying capacity monitoring system based on hydrogeological parameters according to claim 1 is characterized in that: The construction of an environmental carrying capacity evaluation index system based on determining the index weights of environmental carrying capacity evaluation indicators comprises the following steps: Summarize and determine the indicator weights of environmental carrying capacity evaluation indicators and evenly divide the indicator weights of environmental carrying capacity evaluation indicators into three parts: the highest level, the middle level and the lowest level according to the indicator weight order; Compare the weights of indicators in the same part in pairs and build a comparison matrix based on the comparison results; The calculation formula for the comparison result is as follows: Among them, W jk Indicates the indicator weight W j and indicator weight W k The comparison results, ω jk The comparison grade value of the comparison matrix represents the score of the corresponding indicator; Set a selection threshold for the comparison level value, determine the indicators corresponding to the three parts based on the set selection threshold, and record the scores of the corresponding indicators; The indicators corresponding to the three parts are summarized and determined to construct an environmental carrying capacity evaluation index system.

6. The regional environmental carrying capacity monitoring system based on hydrogeological parameters according to claim 1 is characterized in that: The environmental carrying capacity evaluation model is constructed based on the obtained environmental carrying capacity evaluation index system through iterative calculation, and the environmental carrying capacity evaluation model is optimized through deep learning to obtain the optimized environmental carrying capacity evaluation model, which includes the following steps: S31. Construct an environmental carrying capacity assessment model through iterative calculation; S32. Based on the constructed environmental carrying capacity assessment model, set the genetic population size, number of iterations, and chromosome encoding; Each population is set as a set of analyzed historical ecological data of water resources; S33. Randomly select b water resources historical ecological data in each category to generate the initial population S gen ; S34. Use the constructed environmental carrying capacity evaluation model as the fitness function and calculate the fitness of each individual in the population; Assume that each individual represents a set of environmental carrying capacity evaluation index system data; The formula for calculating individual fitness is as follows: Among them, Fit(t) represents the fitness of the t-th individual, and ε represents the environmental carrying capacity evaluation model; S35. Select the best individuals from all individuals based on the roulette wheel method; The calculation formula for selecting the best individual among all individuals in the roulette wheel method is as follows: Among them, p(t) represents the probability of individual t being selected, and T represents the population size; S36, based on the chromosome coding of the selected excellent individuals, cross the selected excellent individuals in a sequential crossover manner, and set the new population generated after the crossover to be S' gen ; S37. Randomly select an individual from the population and mutate it with a set probability. Set the population after the mutation to S” gen ; S38, comparing the fitness difference ΔFit between the initial population and the population after crossover mutation using the genetic algorithm; When ΔFit < 0, it means that the fitness of the mutated population is higher than that of the initial population, and the population is accepted. When ΔFit ≥ 0, it means that the fitness of the mutated population is lower than that of the initial population, and the population is rejected. S39, judging whether the maximum number of iterations has been reached according to the number of iterations of the algorithm, outputting the optimal solution if the maximum number of iterations has been reached, and continuing to execute step S35 if the maximum number of iterations has not been reached; The optimal solution output is set as the optimized environmental carrying capacity assessment model.

7. A regional environmental carrying capacity monitoring system based on hydrogeological parameters according to claim 6, characterized in that: The construction of the environmental carrying capacity assessment model by iterative calculation includes the following steps: The environmental carrying capacity evaluation model is set to consist of various environmental carrying capacity evaluation indicators; The calculation formula of the environmental carrying capacity assessment model is as follows: Among them, WB y (v1',y,v' 2,y ,...,v' m,y ) is the constructed environmental carrying capacity evaluation model, which represents the environmental carrying capacity evaluation results of various indicators in year y, v' m,y represents the mean value of the mth indicator in the yth year, W j ,W k Represents the indicator weights of the jth and kth indicators, v' jy represents the standard value of the jth indicator in the yth year, v' ky It represents the standard value of the kth indicator in the yth year.

8. The regional environmental carrying capacity monitoring system based on hydrogeological parameters according to claim 1 is characterized in that: The summarized and analyzed historical water resource ecological data and the optimized environmental carrying capacity evaluation model are used to predict the environmental carrying capacity score of the hydrogeological parameters in real time through a prediction analysis method, including the following steps: Construct the original time series X (0) =[X (0) 1,X (0) 2,...,X (0) d]; Among them, X (0) d represents the d-th original time series; The environmental carrying capacity scoring formula for the area of ​​real-time prediction of hydrogeological parameters is as follows: in, To analyze the autoregressive coefficient polynomial of the historical ecological data of water resources, is the sliding mean coefficient polynomial of the environmental carrying capacity assessment model, L represents the lag operator, represents the coefficient weight of the qth time series, λ (0) represents a white noise sequence, (1-L) θ The lag operator L represents the θ-order difference of the sequence, Y q represents the environmental carrying capacity score of the qth time series forecast.

9. The regional environmental carrying capacity monitoring system based on hydrogeological parameters according to claim 1 is characterized in that: The process of comparing the environmental carrying capacity scores within the region where the hydrogeological parameters are predicted in real time and determining the environmental carrying capacity scores within the region where the current hydrogeological parameters are determined in real time, and real-time monitoring and management based on the comparison results includes the following steps: Setting a threshold for comparing the environmental carrying capacity score within the region where the hydrogeological parameters are predicted in real time with the environmental carrying capacity score within the region where the current hydrogeological parameters are determined in real time; When the difference between the environmental carrying capacity score in the area where the hydrogeological parameters are predicted in real time and the environmental carrying capacity score in the area where the current hydrogeological parameters are determined in real time is greater than the set comparison result threshold, the collection cycle of water resource ecological data in the area where the hydrogeological parameters are predicted in real time is shortened.

10. A regional environmental carrying capacity monitoring system based on hydrogeological parameters according to any one of claims 1 to 9, characterized in that: include: Data acquisition module, data processing module, data analysis module, evaluation model building module, prediction module and comparison management module; The data acquisition module is used to collect water resource ecological data within the area of ​​hydrogeological parameters; The data processing module is used to process the collected water resources ecological data; The data analysis module is used to analyze the processed water resource ecological data; The evaluation model building module is used to build and determine the evaluation model according to the analysis results; The prediction module is used to make real-time predictions based on the analyzed water resource ecological data and the determined evaluation model; The comparison management module is used to compare the predicted data and the real-time monitoring data, and to adjust the monitoring management cycle of the region of hydrogeological parameters.

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