Cadmium pollution migration rule analysis method and system based on data analysis

Abstract

The invention discloses a data analysis-based cadmium pollution migration rule analysis method and system, and the method comprises the steps: constructing a cadmium pollution migration instance data set, and carrying out the analysis of a cadmium pollution migration rule, so as to obtain first analysis information; carrying out migration influence factor analysis according to the cadmium pollution migration instance data set, and evaluating the influence degree of each influence factor to obtain second analysis information; combining the first analysis information and the second analysis information to analyze a cadmium pollution migration rule under different electric fields, and constructing a migration rule analysis model; acquiring regional soil information, and performing soil condition analysis on target regional soil according to the regional soil information to obtain soil condition analysis information; and making an initial remediation scheme according to the soil condition analysis information, analyzing a cadmium pollution migration rule and remediation benefits of the initial remediation scheme, and optimizing the remediation scheme. By analyzing the migration rule of the cadmium pollution, the migration rule of the cadmium pollution under different electric fields is known, the remediation scheme is optimized, and the remediation effect is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of cadmium pollution migration law analysis, and in particular to a cadmium pollution migration law analysis method and system based on data analysis. Background Art

[0002] Traditional analysis of cadmium pollution migration patterns mostly relies on laboratory analysis. Although this method can provide relatively accurate data, it has many shortcomings. The laboratory analysis cycle is long and it is difficult to reflect changes in pollution conditions in real time. In addition, traditional methods can often only provide local and static pollution information, and lack an in-depth understanding of the dynamic migration and diffusion process of pollutants.

[0003] As an emerging soil remediation method, electric remediation technology removes pollutants by applying an electric field to migrate heavy metal ions in the soil. This technology has the advantages of high remediation efficiency and simple operation, and provides a new means for the treatment of soil cadmium pollution. The migration law of cadmium pollution under different electric fields and environments is analyzed to optimize the working curve and parameters and improve the effect of soil remediation. Summary of the invention

[0004] The present invention overcomes the defects of the prior art and provides a method and system for analyzing the migration law of cadmium pollution based on data analysis, the important purpose of which is to improve the soil remediation effect.

[0005] To achieve the above-mentioned purpose, the present invention provides a method for analyzing the migration law of cadmium pollution based on data analysis in the first aspect, comprising:

[0006] Construct a cadmium pollution migration instance data set, analyze the cadmium pollution migration law, and obtain the first analysis information;

[0007] Analyzing migration influencing factors according to the cadmium pollution migration example data set, and evaluating the influence degree of each influencing factor to obtain second analysis information;

[0008] Combining the first analysis information with the second analysis information, analyzing the migration law of cadmium pollution under different electric fields, and constructing a migration law analysis model;

[0009] Acquire regional soil information, and perform soil condition analysis on the target area soil according to the regional soil information to obtain soil condition analysis information;

[0010] An initial remediation plan is formulated based on the soil condition analysis information, the cadmium pollution migration patterns and remediation benefits of the initial remediation plan are analyzed, and the remediation plan is optimized.

[0011] In this solution, the construction of a cadmium pollution migration example data set and the analysis of cadmium pollution migration rules are as follows:

[0012] Based on big data retrieval, cadmium pollution migration examples under different environments and different electric fields are obtained to form a cadmium pollution migration example data set, and cadmium pollution migration characteristics under each electric field state are extracted to obtain the first characteristic information;

[0013] Performing migration rule analysis according to the first characteristic information, and constructing corresponding migration change trend graphs based on the migration characteristics under different electric fields;

[0014] The migration change trend diagram constructed is used to calculate the migration change amount and change rate of cadmium pollution in different time periods under each electric field. The migration trend of cadmium pollution under different electric fields is analyzed as an analysis indicator to obtain migration trend analysis information.

[0015] Perform abnormal migration detection according to the migration trend analysis information, judge the migration change amount of cadmium pollution in each time period with a preset threshold, analyze the abnormal change trend, and obtain abnormal migration detection information;

[0016] Extracting the corresponding abnormal time period according to the abnormal migration detection information, extracting the corresponding electric field parameters through the first characteristic information and marking them, to obtain abnormal migration analysis information;

[0017] The migration trend analysis information and the abnormal migration analysis information are combined to form the first analysis information.

[0018] In this solution, it is characterized in that the migration influencing factors are analyzed based on the cadmium pollution migration example data set, and the influence degree of each influencing factor is evaluated, specifically:

[0019] Acquire a cadmium pollution migration example data set, extract environmental characteristics under each electric field according to the cadmium pollution migration example data set, and obtain second characteristic information;

[0020] Acquire the first analysis information, perform migration influencing factor analysis in combination with the second feature information, and calculate the Mahalanobis distance between the second feature information and the first feature information based on the Mahalanobis distance algorithm as an influencing factor analysis indicator;

[0021] The calculated Mahalanobis distance is compared with a preset threshold value, and the correlation between each environmental feature and the migration law of cadmium pollution under the corresponding electric field is analyzed according to the judgment result to obtain the correlation analysis information;

[0022] Analyze the influencing factors that affect the migration law of cadmium pollution according to the correlation analysis information, calculate the ratio of the characteristics corresponding to each influencing factor to the total characteristics in combination with the second characteristic information, and construct a probability matrix;

[0023] The entropy weight method is introduced to evaluate the degree of influence. The information entropy of each influencing factor is calculated according to the constructed probability matrix, and the difference coefficient is calculated through the information entropy of each influencing factor.

[0024] The weight of each influencing factor is calculated based on the calculated difference coefficient, and the influence degree of each influencing factor on the migration law is analyzed according to the calculated weight to obtain the influence degree analysis information;

[0025] The correlation analysis information and the influence degree analysis information are combined to form the second analysis information.

[0026] In this solution, it is characterized in that the first analysis information and the second analysis information are combined to analyze the migration law of cadmium pollution under different electric fields, and to construct a migration law analysis model, specifically:

[0027] Obtaining first analysis information and second analysis information, analyzing the migration law of cadmium pollution under different electric fields according to the first analysis information and the second analysis information, and constructing a migration law knowledge graph;

[0028] A migration law analysis model was built based on the migration law knowledge graph and the cadmium pollution migration case data set, and the Markov algorithm was introduced to build the model;

[0029] Constructing a state space according to the migration law knowledge graph, defining the migration state of cadmium pollution according to the migration laws under different environments and different electric fields, each migration state represents an independent migration law;

[0030] The state transition probability is calculated based on the cadmium pollution migration instance data set, and the probability of each state in the state space transferring to the next state is calculated by analyzing the historical data in the cadmium pollution migration instance data set to obtain the state transition probability;

[0031] Constructing a transition probability matrix according to the state transition probability, modifying the constructed transition probability matrix based on the expert analysis method, setting the initial state probability distribution, and constructing a migration law analysis model in combination with the state space and the transition probability matrix;

[0032] A training data set is constructed based on the migration law knowledge graph and the cadmium pollution migration instance data set to perform deep learning and training on the migration law analysis model to obtain a migration law analysis model that meets the expectations.

[0033] In this solution, it is characterized in that the acquisition of regional soil information and the analysis of soil conditions of the target area soil according to the regional soil information are specifically as follows:

[0034] Sampling the soil in the target area, obtaining soil samples at different locations and depths, analyzing the soil indicators in each sample based on soil testing technology, and obtaining regional soil information;

[0035] Based on big data retrieval, several soil condition assessment indicators are obtained, and the Pearson correlation coefficient between each assessment indicator and the corresponding soil condition is calculated as a correlation analysis indicator;

[0036] The calculated correlation analysis index is judged against the preset threshold, and the corresponding evaluation index is selected according to the judgment result to obtain the evaluation index information;

[0037] Based on the expert knowledge method, the influence score of each evaluation indicator is obtained according to the evaluation indicator information, the intuitive fuzzy analysis method is introduced to assign weights to each evaluation indicator, and an intuitive fuzzy matrix is ​​constructed according to the influence score;

[0038] Calculating the intuitionistic fuzzy entropy of each evaluation indicator according to the intuitionistic fuzzy matrix, calculating the intuitionistic fuzzy number of each evaluation indicator through the intuitionistic fuzzy entropy, assigning weights to each evaluation indicator, and obtaining evaluation indicator weight information;

[0039] Constructing a soil condition analysis model based on the evaluation index weight information, inputting the regional soil information into the soil condition analysis model for analysis, and obtaining soil condition analysis information;

[0040] Extracting sampling positions of each sampling point according to the regional soil information to divide the target area into multiple sub-areas, extracting soil condition characteristics of each sub-area through the soil condition analysis information to obtain soil condition characteristic information of the sub-area;

[0041] A soil condition grade division threshold is preset, the soil condition characteristic information of the sub-region is judged with the soil condition grade division threshold, grade division is performed according to the judgment result, and adjacent sub-regions of the same grade are merged to obtain regional soil division information.

[0042] This solution is characterized in that an initial remediation plan is formulated based on the soil condition analysis information, the cadmium pollution migration law and remediation benefits of the initial remediation plan are analyzed, and the remediation plan is optimized, specifically:

[0043] Obtain soil condition analysis information and regional soil classification information, obtain restoration plan examples for various soil conditions based on big data retrieval, and form a restoration plan example data set;

[0044] Calculate the similarity between the soil condition analysis information, the regional soil division information and the restoration scheme instance data set, and make a judgment with a preset threshold, and formulate an initial restoration scheme according to the judgment result;

[0045] Inputting the soil condition analysis information and the initial remediation plan into the migration law analysis model for analysis, analyzing and predicting the cadmium pollution migration law of each remediation plan, and obtaining migration law prediction information;

[0046] Calculating the repair time of the corresponding initial repair plan according to the migration law prediction information, and calculating the consumption cost of each repair plan, performing a repair benefit analysis, and obtaining repair benefit analysis information;

[0047] Determine whether the corresponding restoration plan can be adopted according to the restoration benefit analysis information, and if not, optimize the restoration plan;

[0048] Extracting all restoration schemes under similar soil conditions from the restoration scheme example data set through the soil condition analysis information and the regional soil division information to perform restoration benefit analysis, thereby obtaining first restoration benefit analysis information;

[0049] Preset optimization goals and screening rules, and screen corresponding plans in combination with the first restoration benefit analysis information to obtain candidate optimization plans;

[0050] Feature extraction is performed on candidate optimization schemes to analyze the differences in characteristics with the initial remediation scheme. An optimization scheme is formulated based on the differences in characteristics and migration law analysis and remediation benefit analysis are performed. Based on the analysis results, the best optimization scheme is selected for soil remediation.

[0051] A second aspect of the present invention provides a cadmium pollution migration law analysis system based on data analysis, the system comprising: a memory, a processor, the memory containing a cadmium pollution migration law analysis method program based on data analysis, the cadmium pollution migration law analysis method program based on data analysis when executed by the processor to implement the following steps:

[0052] Construct a cadmium pollution migration instance data set, analyze the cadmium pollution migration law, and obtain the first analysis information;

[0053] Analyzing migration influencing factors according to the cadmium pollution migration example data set, and evaluating the influence degree of each influencing factor to obtain second analysis information;

[0054] Combining the first analysis information with the second analysis information, analyzing the migration law of cadmium pollution under different electric fields, and constructing a migration law analysis model;

[0055] Acquire regional soil information, and perform soil condition analysis on the target area soil according to the regional soil information to obtain soil condition analysis information;

[0056] An initial remediation plan is formulated based on the soil condition analysis information, the cadmium pollution migration patterns and remediation benefits of the initial remediation plan are analyzed, and the remediation plan is optimized.

[0057] The present invention discloses a method and system for analyzing the migration law of cadmium pollution based on data analysis, including: constructing a cadmium pollution migration instance data set, analyzing the migration law of cadmium pollution, and obtaining first analysis information; analyzing migration influencing factors according to the cadmium pollution migration instance data set, and evaluating the influence degree of each influencing factor to obtain second analysis information; analyzing the migration law of cadmium pollution under different electric fields in combination with the first analysis information and the second analysis information, and constructing a migration law analysis model; obtaining regional soil information, analyzing the soil condition of the target area soil according to the regional soil information, and obtaining soil condition analysis information; formulating an initial remediation plan according to the soil condition analysis information, analyzing the cadmium pollution migration law and remediation benefit of the initial remediation plan, and optimizing the remediation plan. By analyzing the migration law of cadmium pollution, the migration law of cadmium pollution under different electric fields can be understood, the remediation plan can be optimized, and the remediation effect can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions in the embodiments or exemplary embodiments of the present invention, the drawings required for use in the embodiments or exemplary descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained according to the drawings without paying creative work.

[0059] Figure 1 A flow chart of a method for analyzing cadmium pollution migration rules based on data analysis provided by one embodiment of the present invention;

[0060] Figure 2 A flowchart of the repair solution optimization provided by an embodiment of the present invention;

[0061] Figure 3 A block diagram of a cadmium pollution migration law analysis system based on data analysis provided by one embodiment of the present invention;

[0062] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0063] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0064] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0065] Figure 1 A flow chart of a method for analyzing cadmium pollution migration rules based on data analysis provided by one embodiment of the present invention;

[0066] like Figure 1 As shown, the present invention provides a flow chart of a method for analyzing the migration law of cadmium pollution based on data analysis, comprising:

[0067] S102, constructing a cadmium pollution migration instance data set, analyzing the cadmium pollution migration law, and obtaining first analysis information;

[0068] S104, analyzing migration influencing factors according to the cadmium pollution migration example data set, and evaluating the influence degree of each influencing factor to obtain second analysis information;

[0069] S106, analyzing the migration law of cadmium pollution under different electric fields by combining the first analysis information and the second analysis information, and constructing a migration law analysis model;

[0070] S108, acquiring regional soil information, and performing soil condition analysis on the target regional soil according to the regional soil information to obtain soil condition analysis information;

[0071] S110, formulating an initial remediation plan based on the soil condition analysis information, analyzing the cadmium pollution migration pattern and remediation benefits of the initial remediation plan, and optimizing the remediation plan.

[0072] It should be noted that the present invention provides a method for analyzing the migration law of cadmium pollution based on data analysis. By analyzing the migration law of cadmium pollution under different environments and electric fields through historical data, the influence and law of electric fields of different intensities on the migration of cadmium pollution in different soil environments can be understood. A migration law analysis model is constructed based on the analysis results, and an adaptive plan is formulated according to the soil environment of the target area. The migration law and restoration benefits of each plan are analyzed to determine whether optimization is needed. Improve the restoration effect of cadmium pollution by electric restoration.

[0073] Further, in a preferred embodiment of the present invention, the step of constructing a cadmium pollution migration example data set and analyzing the cadmium pollution migration rules specifically includes:

[0074] Based on big data retrieval, cadmium pollution migration examples under different environments and different electric fields are obtained to form a cadmium pollution migration example data set, and cadmium pollution migration characteristics under each electric field state are extracted to obtain the first characteristic information;

[0075] Performing migration rule analysis according to the first characteristic information, and constructing corresponding migration change trend graphs based on the migration characteristics under different electric fields;

[0076] The migration change trend diagram constructed is used to calculate the migration change amount and change rate of cadmium pollution in different time periods under each electric field. The migration trend of cadmium pollution under different electric fields is analyzed as an analysis indicator to obtain migration trend analysis information.

[0077] Perform abnormal migration detection according to the migration trend analysis information, judge the migration change amount of cadmium pollution in each time period with a preset threshold, analyze the abnormal change trend, and obtain abnormal migration detection information;

[0078] Extracting the corresponding abnormal time period according to the abnormal migration detection information, extracting the corresponding electric field parameters through the first characteristic information and marking them, to obtain abnormal migration analysis information;

[0079] The migration trend analysis information and the abnormal migration analysis information are combined to form the first analysis information.

[0080] It should be noted that based on the big data retrieval, cadmium pollution migration examples under different environments and electric field conditions are obtained to form a cadmium pollution migration example data set. The different environments correspond to different soil environments, and the different electric fields correspond to different electric field strengths, layouts, etc. used when performing electric remediation of cadmium pollution. By extracting features from the cadmium pollution migration example data set, extracting the corresponding migration features and constructing a migration change trend chart, the migration change amount and change rate of cadmium pollution in different time periods under each electric field are calculated, so as to analyze the migration law of cadmium pollution. Next, abnormal migration detection is performed. When performing electric remediation of cadmium pollution, different electric field layouts are used under different environments, and different electric field strengths are set according to demand to improve the corresponding remediation effect and rate. For cadmium pollution migration, the strength of the electric field is related to it. The change in electric field strength will not only accelerate the migration of cadmium pollution, but also slow down the migration of cadmium pollution due to excessive electric fields, reducing the remediation effect and efficiency. By performing abnormal migration detection, the abnormal migration of cadmium pollution under various environments can be found, thereby finding the corresponding abnormal electric field parameters, providing a basis for subsequent analysis.

[0081] Furthermore, in a preferred embodiment of the present invention, the migration influencing factors analysis is performed based on the cadmium pollution migration example data set, and the influence degree of each influencing factor is evaluated, specifically including:

[0082] Acquire a cadmium pollution migration example data set, extract environmental characteristics under each electric field according to the cadmium pollution migration example data set, and obtain second characteristic information;

[0083] Acquire the first analysis information, perform migration influencing factor analysis in combination with the second feature information, and calculate the Mahalanobis distance between the second feature information and the first feature information based on the Mahalanobis distance algorithm as an influencing factor analysis indicator;

[0084] The calculated Mahalanobis distance is compared with a preset threshold value, and the correlation between each environmental feature and the migration law of cadmium pollution under the corresponding electric field is analyzed according to the judgment result to obtain the correlation analysis information;

[0085] Analyze the influencing factors that affect the migration law of cadmium pollution according to the correlation analysis information, calculate the ratio of the characteristics corresponding to each influencing factor to the total characteristics in combination with the second characteristic information, and construct a probability matrix;

[0086] The entropy weight method is introduced to evaluate the degree of influence. The information entropy of each influencing factor is calculated according to the constructed probability matrix, and the difference coefficient is calculated through the information entropy of each influencing factor.

[0087] The weight of each influencing factor is calculated based on the calculated difference coefficient, and the influence degree of each influencing factor on the migration law is analyzed according to the calculated weight to obtain the influence degree analysis information;

[0088] The correlation analysis information and the influence degree analysis information are combined to form the second analysis information.

[0089] It should be noted that in the analysis of migration rules, the migration of cadmium pollution is not only affected by the electric field, but also by different environments. First, obtain a data set of cadmium pollution migration examples, and extract environmental characteristics under each electric field from it. These characteristics include soil type, humidity, pH value, etc., which constitute the second characteristic information. These characteristic information provide basic data for us to analyze the influencing factors of cadmium pollution migration. Next, the first analysis information, that is, the overall trend of cadmium pollution migration and abnormal migration, is compared and analyzed with the second characteristic information. The Mahalanobis distance algorithm is used to calculate the Mahalanobis distance between the second characteristic information and the first characteristic information as a key indicator for judging the importance of influencing factors. The calculated distance is compared with the preset threshold, and the correlation between each environmental feature and the migration law of cadmium pollution under the corresponding electric field is analyzed to reveal which environmental factors are closely related to the migration law of cadmium pollution. Then, the ratio of the characteristics corresponding to each influencing factor to the total characteristics is calculated, and a probability matrix is ​​constructed. This matrix intuitively shows the relative importance of each factor in affecting the migration of cadmium pollution. The entropy weight method is introduced to evaluate the degree of influence of each influencing factor. Based on the constructed probability matrix, the information entropy and difference coefficient of each influencing factor are calculated. These coefficients of variation reflect the differences in the impact of various factors on the migration of cadmium pollution. Finally, the weights of various influencing factors are determined based on the calculated coefficients of variation, and the weights reflect the degree of influence of each factor on the migration law.

[0090] Further, in a preferred embodiment of the present invention, the first analysis information and the second analysis information are combined to analyze the migration law of cadmium pollution under different electric fields, and a migration law analysis model is constructed, which specifically includes:

[0091] Obtaining first analysis information and second analysis information, analyzing the migration law of cadmium pollution under different electric fields according to the first analysis information and the second analysis information, and constructing a migration law knowledge graph;

[0092] A migration law analysis model was built based on the migration law knowledge graph and the cadmium pollution migration case data set, and the Markov algorithm was introduced to build the model;

[0093] Constructing a state space according to the migration law knowledge graph, defining the migration state of cadmium pollution according to the migration laws under different environments and different electric fields, each migration state represents an independent migration law;

[0094] The state transition probability is calculated based on the cadmium pollution migration instance data set, and the probability of each state in the state space transferring to the next state is calculated by analyzing the historical data in the cadmium pollution migration instance data set to obtain the state transition probability;

[0095] Constructing a transition probability matrix according to the state transition probability, modifying the constructed transition probability matrix based on the expert analysis method, setting the initial state probability distribution, and constructing a migration law analysis model in combination with the state space and the transition probability matrix;

[0096] A training data set is constructed based on the migration law knowledge graph and the cadmium pollution migration instance data set to perform deep learning and training on the migration law analysis model to obtain a migration law analysis model that meets the expectations.

[0097] It should be noted that, first, the overall trend of cadmium pollution migration, abnormal migration and key factors affecting migration are understood according to the first analysis information and the second analysis information, and the migration law analysis is performed. Based on the first analysis information and the second analysis information, a migration law knowledge graph is constructed to show the relationship and degree of influence between the migration law of cadmium pollution and its influencing factors under different electric fields. Then, the migration law analysis model is constructed using the migration law knowledge graph and the cadmium pollution migration example data set. The Markov algorithm is introduced, which can predict future migration trends based on the current state to analyze the migration law of cadmium pollution. The state space is constructed according to the migration law knowledge graph. In this state space, each state represents the migration law of cadmium pollution under a specific environment and electric field. By defining these states, the migration of cadmium pollution can be analyzed more systematically. The states in the migration law analysis can represent different migration situations, locations or stages, etc. For example, the states can be different directions, speeds, etc. The state space should be comprehensive and non-overlapping to ensure that all possible migration situations can be covered by these states and each state represents a unique situation. Then, the state transition probability is calculated using the cadmium pollution migration instance data set, reflecting the possibility of cadmium pollution transferring from one migration state to another under a specific environment and electric field. The transition probability matrix is ​​constructed based on the calculated state transition probability. The expert analysis method is used to correct it to ensure the accuracy of the matrix. At the same time, the initial state probability distribution is set, which describes the state distribution of the random process at the starting time, that is, the probability of each state being occupied at the starting time. This distribution is an important starting point for random process analysis, which determines the basis for subsequent state transition and evolution. The transition probability matrix is ​​a key component, in which each element represents the probability of transitioning from one state to another. The sum of the probabilities of each row is equal to 1, ensuring that the new state is transferred at each time step. And the matrix elements are non-negative numbers to avoid negative probabilities. Finally, the migration law analysis model is constructed by combining the state space, the transition probability matrix and the initial state probability distribution. The training data set is constructed using the migration law knowledge graph and the cadmium pollution migration instance data set, and the model is deeply learned and trained. The validation set and test set are constructed to test and verify the model, so as to obtain a model that meets the expectations. Reveal the migration patterns of cadmium pollution under different electric fields and provide strong technical support for soil remediation and environmental protection.

[0098] Furthermore, in a preferred embodiment of the present invention, the acquiring of regional soil information and the analysis of soil conditions of the target regional soil according to the regional soil information specifically include:

[0099] Sampling the soil in the target area, obtaining soil samples at different locations and depths, analyzing the soil indicators in each sample based on soil testing technology, and obtaining regional soil information;

[0100] Based on big data retrieval, several soil condition assessment indicators are obtained, and the Pearson correlation coefficient between each assessment indicator and the corresponding soil condition is calculated as a correlation analysis indicator;

[0101] The calculated correlation analysis index is judged against the preset threshold, and the corresponding evaluation index is selected according to the judgment result to obtain the evaluation index information;

[0102] Based on the expert knowledge method, the influence score of each evaluation indicator is obtained according to the evaluation indicator information, the intuitive fuzzy analysis method is introduced to assign weights to each evaluation indicator, and an intuitive fuzzy matrix is ​​constructed according to the influence score;

[0103] Calculating the intuitionistic fuzzy entropy of each evaluation indicator according to the intuitionistic fuzzy matrix, calculating the intuitionistic fuzzy number of each evaluation indicator through the intuitionistic fuzzy entropy, assigning weights to each evaluation indicator, and obtaining evaluation indicator weight information;

[0104] Constructing a soil condition analysis model based on the evaluation index weight information, inputting the regional soil information into the soil condition analysis model for analysis, and obtaining soil condition analysis information;

[0105] Extracting sampling positions of each sampling point according to the regional soil information to divide the target area into multiple sub-areas, extracting soil condition characteristics of each sub-area through the soil condition analysis information to obtain soil condition characteristic information of the sub-area;

[0106] A soil condition grade division threshold is preset, the soil condition characteristic information of the sub-region is judged with the soil condition grade division threshold, grade division is performed according to the judgment result, and adjacent sub-regions of the same grade are merged to obtain regional soil division information.

[0107] It should be noted that before the electric remediation of the target area, it is necessary to analyze the soil conditions of the target area to determine the cadmium pollution status and soil conditions of the target area. By sampling the target area and testing the sampled samples based on soil detection technology, the various soil indicators in each sample, such as organic matter content, pH value, heavy metal content, etc., are deeply analyzed to obtain detailed regional soil information. Then, based on big data retrieval, several soil condition evaluation indicators are obtained, the Pearson correlation coefficient between these evaluation indicators and the corresponding soil conditions is calculated, the degree of correlation between the quantitative indicators and the soil conditions is quantified, and it is compared with the preset threshold to screen out those evaluation indicators that are highly correlated with the soil conditions, thereby ensuring the accuracy and effectiveness of subsequent analysis. The expert knowledge method and the intuitive fuzzy analysis method are introduced for weight setting, and the weights of each evaluation indicator are scientifically assigned to obtain the evaluation indicator weight information. Then, the target area is divided into multiple sub-areas according to the location of the sampling point. Through the soil condition analysis information, the soil condition characteristics of each sub-area are extracted to obtain the soil condition characteristic information of the sub-area. Finally, a soil condition classification threshold is preset, and the soil condition characteristic information of the sub-region is compared with the threshold. Each sub-region is classified, and adjacent sub-regions of the same level are merged to finally obtain regional soil classification information, which provides a basis for the subsequent formulation and optimization of restoration plans.

[0108] Further, in a preferred embodiment of the present invention, the initial remediation plan is formulated according to the soil condition analysis information, the cadmium pollution migration law and remediation benefit of the initial remediation plan are analyzed, and the remediation plan is optimized, specifically including:

[0109] Obtain soil condition analysis information and regional soil classification information, obtain restoration plan examples for various soil conditions based on big data retrieval, and form a restoration plan example data set;

[0110] Calculate the similarity between the soil condition analysis information, the regional soil division information and the restoration scheme instance data set, and make a judgment with a preset threshold, and formulate an initial restoration scheme according to the judgment result;

[0111] Inputting the soil condition analysis information and the initial remediation plan into the migration law analysis model for analysis, analyzing and predicting the cadmium pollution migration law of each remediation plan, and obtaining migration law prediction information;

[0112] Calculating the repair time of the corresponding initial repair plan according to the migration law prediction information, and calculating the consumption cost of each repair plan, performing a repair benefit analysis, and obtaining repair benefit analysis information;

[0113] Determine whether the corresponding restoration plan can be adopted according to the restoration benefit analysis information, and if not, optimize the restoration plan;

[0114] Extracting all restoration schemes under similar soil conditions from the restoration scheme example data set through the soil condition analysis information and the regional soil division information to perform restoration benefit analysis, thereby obtaining first restoration benefit analysis information;

[0115] Preset optimization goals and screening rules, and screen corresponding plans in combination with the first restoration benefit analysis information to obtain candidate optimization plans;

[0116] Feature extraction is performed on candidate optimization schemes to analyze the differences in characteristics with the initial remediation scheme. An optimization scheme is formulated based on the differences in characteristics and migration law analysis and remediation benefit analysis are performed. Based on the analysis results, the best optimization scheme is selected for soil remediation.

[0117] It should be noted that, first, the big data retrieval technology is used to collect examples of remediation schemes for various soil conditions and construct a remediation scheme example data set. The soil condition analysis information, regional soil division information and the remediation scheme example data set are similarity calculated. By comparing the similarity between them and judging with the preset threshold, the remediation scheme that matches the current soil condition is preliminarily screened out to form an initial remediation scheme. Then, for the initial remediation scheme, the migration law of each initial remediation scheme is analyzed and predicted by the migration analysis model. The soil condition analysis information and the initial remediation scheme are input into the migration law analysis model to analyze and predict the migration law of cadmium pollution under each remediation scheme. The remediation time and consumption cost of the corresponding initial remediation scheme are further calculated, and the remediation benefit analysis is performed to obtain the remediation benefit analysis information, which provides an important basis for judging the feasibility of the remediation scheme. The judgment criteria are set according to the needs, such as the need for good remediation effect or short remediation time, etc. If the corresponding initial remediation scheme cannot be adopted, the remediation scheme needs to be optimized. At this stage, the soil condition analysis information and regional soil division information are used again to extract all remediation schemes under similar soil conditions from the remediation scheme example data set, and the remediation benefit analysis is performed to obtain the first remediation benefit analysis information. In order to screen out the best candidate optimization schemes, preset optimization goals and screening rules, such as optimization goals such as restoration time and cost. Combined with the first restoration benefit analysis information, screen out candidate optimization schemes that meet the requirements. Subsequently, feature extraction is performed on the candidate optimization schemes, and their difference characteristics from the initial restoration schemes are deeply analyzed. Based on these difference characteristics, a specific optimization scheme is formulated, such as replacing and optimizing the electric field strength difference characteristics with the electric field strength characteristics used in the initial scheme, and migration law analysis and restoration benefit analysis are performed again to judge the feasibility of the optimization scheme, and finally the best optimization scheme is selected for soil restoration, thereby improving the restoration effect and efficiency.

[0118] Figure 2A flowchart of the repair solution optimization provided by an embodiment of the present invention;

[0119] like Figure 2 As shown, the present invention provides a repair solution optimization flow chart, including:

[0120] S202, sampling the soil in the target area, obtaining soil samples at different locations and depths, and analyzing soil indicators in each sample based on soil detection technology;

[0121] S204, inputting the regional soil information into a soil condition analysis model for analysis, and dividing the target area according to the soil condition analysis results;

[0122] S206, calculating the similarity between the soil condition analysis information, the regional soil division information and the restoration plan instance data set, formulating an initial restoration plan, and performing restoration benefit analysis;

[0123] S208, judging whether the corresponding restoration plan can be adopted according to the restoration benefit analysis information, and if not, optimizing the restoration plan;

[0124] S210, extract all repair solution instances under similar environments, analyze the difference characteristics from the initial repair solution, optimize the solution according to the difference characteristics, perform repair benefit analysis on the optimized solution, and select the best optimized solution according to the analysis results.

[0125] It should be noted that in the process of formulating and optimizing the restoration plan, the environmental characteristics of the target area are fixed characteristics. Through this fixed characteristic, many restoration plans under similar environments can be obtained, and then the initial restoration plan is selected. At this time, the initial restoration plan also needs to be analyzed for restoration benefits before it can be used. If it cannot be used, it needs to be optimized by selecting all restoration plan instances under the environmental characteristics and extracting and analyzing the corresponding difference characteristics. At this time, the difference characteristics represent the electric field strength, gradient, electric field layout, etc. The initial plan is optimized through the difference characteristics to obtain the candidate plan. Next, for the optimization of the plan, it is necessary to consider not only the feasibility of the plan, but also the actual needs, such as the need for good restoration effect and short time, etc. By performing restoration benefit analysis on the optimization plan, the optimization plan that meets the feasibility and needs is selected to improve the restoration effect.

[0126] In addition, the method for analyzing the migration law of cadmium pollution based on data analysis also includes the following steps:

[0127] Acquire soil monitoring information of a target area, input the soil monitoring information of the target area into the soil condition analysis model for analysis, and obtain first soil condition analysis information;

[0128] Dividing the target area according to the first soil condition analysis information to obtain area division information;

[0129] Inputting the first soil condition analysis information and the regional division information into a migration law analysis model for analysis, analyzing the migration law of cadmium pollution in each region, and obtaining cadmium pollution migration law analysis information;

[0130] Extract the migration direction and trend of cadmium pollution in each region according to the cadmium pollution migration law analysis information, conduct cadmium pollution migration change analysis, connect adjacent regions with the same migration direction and trend, and draw a cadmium pollution migration path map;

[0131] Conduct pollution source tracing according to the cadmium pollution migration path map, determine the pollution source according to the cadmium pollution migration path, and obtain pollution source tracing analysis information;

[0132] According to the pollution source tracing analysis information, the geographic information of the target area is obtained, the attribute characteristics of each building in the target area are extracted, the attribute characteristics of each building are analyzed, and the buildings are screened according to the attribute analysis results, and the buildings that meet the pollution generation requirements are analyzed to obtain the screening result information;

[0133] An early warning is issued based on the screening result information, prompting an abnormal emission investigation.

[0134] Figure 3 A cadmium pollution migration law analysis system 3 based on data analysis is provided in one embodiment of the present invention. The system comprises: a memory 31 and a processor 32. The memory 31 contains a cadmium pollution migration law analysis method program based on data analysis. When the cadmium pollution migration law analysis method program based on data analysis is executed by the processor 32, the following steps are implemented:

[0135] Construct a cadmium pollution migration instance data set, analyze the cadmium pollution migration law, and obtain the first analysis information;

[0136] Analyzing migration influencing factors according to the cadmium pollution migration example data set, and evaluating the influence degree of each influencing factor to obtain second analysis information;

[0137] Combining the first analysis information with the second analysis information, analyzing the migration law of cadmium pollution under different electric fields, and constructing a migration law analysis model;

[0138] Acquire regional soil information, and perform soil condition analysis on the target area soil according to the regional soil information to obtain soil condition analysis information;

[0139] An initial remediation plan is formulated based on the soil condition analysis information, the cadmium pollution migration patterns and remediation benefits of the initial remediation plan are analyzed, and the remediation plan is optimized.

[0140] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0141] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0142] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0143] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks or optical disks, and other media that can store program codes.

[0144] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0145] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for analyzing the migration law of cadmium pollution based on data analysis, characterized in that: include: Construct a cadmium pollution migration instance data set, analyze the cadmium pollution migration law, and obtain the first analysis information; Analyzing migration influencing factors according to the cadmium pollution migration example data set, and evaluating the influence degree of each influencing factor to obtain second analysis information; Combining the first analysis information and the second analysis information, analyzing the migration law of cadmium pollution under different electric fields, and constructing a migration law analysis model; Acquire regional soil information, and perform soil condition analysis on the target area soil according to the regional soil information to obtain soil condition analysis information; An initial remediation plan is formulated based on the soil condition analysis information, the cadmium pollution migration patterns and remediation benefits of the initial remediation plan are analyzed, and the remediation plan is optimized.

2. The method for analyzing cadmium pollution migration rules based on data analysis according to claim 1, characterized in that: The construction of a cadmium pollution migration example data set and the analysis of cadmium pollution migration rules specifically include: Based on big data retrieval, cadmium pollution migration examples under different environments and different electric fields are obtained to form a cadmium pollution migration example data set, and cadmium pollution migration characteristics under each electric field state are extracted to obtain the first characteristic information; Performing migration rule analysis according to the first characteristic information, and constructing corresponding migration change trend graphs based on the migration characteristics under different electric fields; The migration change trend diagram constructed is used to calculate the migration change amount and change rate of cadmium pollution in different time periods under each electric field. The migration trend of cadmium pollution under different electric fields is analyzed as an analysis indicator to obtain migration trend analysis information. Perform abnormal migration detection according to the migration trend analysis information, judge the migration change amount of cadmium pollution in each time period with a preset threshold, analyze the abnormal change trend, and obtain abnormal migration detection information; Extracting the corresponding abnormal time period according to the abnormal migration detection information, extracting the corresponding electric field parameters through the first characteristic information and marking them, to obtain abnormal migration analysis information; The migration trend analysis information and the abnormal migration analysis information are combined to form the first analysis information.

3. The method for analyzing cadmium pollution migration rules based on data analysis according to claim 1, characterized in that: The migration influencing factors analysis is performed based on the cadmium pollution migration example data set, and the influence degree of each influencing factor is evaluated, specifically including: Acquire a cadmium pollution migration example data set, extract environmental characteristics under each electric field according to the cadmium pollution migration example data set, and obtain second characteristic information; Acquire the first analysis information, perform migration influencing factor analysis in combination with the second feature information, and calculate the Mahalanobis distance between the second feature information and the first feature information based on the Mahalanobis distance algorithm as an influencing factor analysis indicator; The calculated Mahalanobis distance is compared with a preset threshold value, and the correlation between each environmental feature and the migration law of cadmium pollution under the corresponding electric field is analyzed according to the judgment result to obtain the correlation analysis information; Analyze the influencing factors that affect the migration law of cadmium pollution according to the correlation analysis information, calculate the ratio of the characteristics corresponding to each influencing factor to the total characteristics in combination with the second characteristic information, and construct a probability matrix; The entropy weight method is introduced to evaluate the degree of influence. The information entropy of each influencing factor is calculated according to the constructed probability matrix, and the difference coefficient is calculated through the information entropy of each influencing factor. The weight of each influencing factor is calculated based on the calculated difference coefficient, and the influence degree of each influencing factor on the migration law is analyzed according to the calculated weight to obtain the influence degree analysis information; The correlation analysis information and the influence degree analysis information are combined to form the second analysis information.

4. The method for analyzing cadmium pollution migration rules based on data analysis according to claim 1, characterized in that: The combining of the first analysis information and the second analysis information to analyze the migration law of cadmium pollution under different electric fields and constructing a migration law analysis model specifically includes: Obtaining first analysis information and second analysis information, analyzing the migration law of cadmium pollution under different electric fields according to the first analysis information and the second analysis information, and constructing a migration law knowledge graph; A migration law analysis model was built based on the migration law knowledge graph and the cadmium pollution migration case data set, and the Markov algorithm was introduced to build the model; Constructing a state space according to the migration law knowledge graph, defining the migration state of cadmium pollution according to the migration laws under different environments and different electric fields, each migration state represents an independent migration law; The state transition probability is calculated based on the cadmium pollution migration instance data set, and the probability of each state in the state space transferring to the next state is calculated by analyzing the historical data in the cadmium pollution migration instance data set to obtain the state transition probability; Constructing a transition probability matrix according to the state transition probability, modifying the constructed transition probability matrix based on the expert analysis method, setting the initial state probability distribution, and constructing a migration law analysis model in combination with the state space and the transition probability matrix; A training data set is constructed based on the migration law knowledge graph and the cadmium pollution migration instance data set to perform deep learning and training on the migration law analysis model to obtain a migration law analysis model that meets the expectations.

5. The method for analyzing cadmium pollution migration rules based on data analysis according to claim 1, characterized in that: The acquiring of regional soil information and performing soil condition analysis on the target regional soil according to the regional soil information specifically includes: Sampling the soil in the target area, obtaining soil samples at different locations and depths, analyzing the soil indicators in each sample based on soil testing technology, and obtaining regional soil information; Based on big data retrieval, several soil condition assessment indicators are obtained, and the Pearson correlation coefficient between each assessment indicator and the corresponding soil condition is calculated as a correlation analysis indicator; The calculated correlation analysis index is judged against the preset threshold, and the corresponding evaluation index is selected according to the judgment result to obtain the evaluation index information; Based on the expert knowledge method, the influence score of each evaluation indicator is obtained according to the evaluation indicator information, the intuitive fuzzy analysis method is introduced to assign weights to each evaluation indicator, and the intuitive fuzzy matrix is ​​constructed according to the influence score; Calculating the intuitionistic fuzzy entropy of each evaluation indicator according to the intuitionistic fuzzy matrix, calculating the intuitionistic fuzzy number of each evaluation indicator through the intuitionistic fuzzy entropy, assigning weights to each evaluation indicator, and obtaining evaluation indicator weight information; Constructing a soil condition analysis model based on the evaluation index weight information, inputting the regional soil information into the soil condition analysis model for analysis, and obtaining soil condition analysis information; Extracting sampling positions of each sampling point according to the regional soil information to divide the target area into multiple sub-areas, extracting soil condition characteristics of each sub-area through the soil condition analysis information to obtain soil condition characteristic information of the sub-area; A soil condition grade division threshold is preset, the soil condition characteristic information of the sub-region is judged with the soil condition grade division threshold, grade division is performed according to the judgment result, and adjacent sub-regions of the same grade are merged to obtain regional soil division information.

6. The method for analyzing cadmium pollution migration rules based on data analysis according to claim 1, characterized in that: The initial remediation plan is formulated based on the soil condition analysis information, the cadmium pollution migration law and remediation benefits of the initial remediation plan are analyzed, and the remediation plan is optimized, specifically including: Obtain soil condition analysis information and regional soil classification information, obtain restoration plan examples for various soil conditions based on big data retrieval, and form a restoration plan example data set; Calculate the similarity between the soil condition analysis information, the regional soil division information and the restoration scheme instance data set, and make a judgment with a preset threshold, and formulate an initial restoration scheme according to the judgment result; Inputting the soil condition analysis information and the initial remediation plan into the migration law analysis model for analysis, analyzing and predicting the cadmium pollution migration law of each remediation plan, and obtaining migration law prediction information; Calculating the repair time of the corresponding initial repair plan according to the migration law prediction information, and calculating the consumption cost of each repair plan, performing a repair benefit analysis, and obtaining repair benefit analysis information; Determine whether the corresponding restoration plan can be adopted according to the restoration benefit analysis information, and if not, optimize the restoration plan; Extracting all restoration schemes under similar soil conditions from the restoration scheme example data set through the soil condition analysis information and the regional soil division information to perform restoration benefit analysis, thereby obtaining first restoration benefit analysis information; Preset optimization goals and screening rules, and screen corresponding plans in combination with the first restoration benefit analysis information to obtain candidate optimization plans; Feature extraction is performed on candidate optimization schemes to analyze the differences in characteristics with the initial remediation scheme. An optimization scheme is formulated based on the differences in characteristics and migration law analysis and remediation benefit analysis are performed. Based on the analysis results, the best optimization scheme is selected for soil remediation.

7. A cadmium pollution migration law analysis system based on data analysis, characterized in that: The system includes: a memory and a processor, wherein the memory contains a cadmium pollution migration law analysis method program based on data analysis, and when the cadmium pollution migration law analysis method program based on data analysis is executed by the processor, the following steps are implemented: Construct a cadmium pollution migration instance data set, analyze the cadmium pollution migration law, and obtain the first analysis information; Analyzing migration influencing factors according to the cadmium pollution migration example data set, and evaluating the influence degree of each influencing factor to obtain second analysis information; Combining the first analysis information and the second analysis information, analyzing the migration law of cadmium pollution under different electric fields, and constructing a migration law analysis model; Acquire regional soil information, and perform soil condition analysis on the target area soil according to the regional soil information to obtain soil condition analysis information; An initial remediation plan is formulated based on the soil condition analysis information, the cadmium pollution migration patterns and remediation benefits of the initial remediation plan are analyzed, and the remediation plan is optimized.

8. The cadmium pollution migration law analysis system based on data analysis according to claim 7, characterized in that: The construction of a cadmium pollution migration example data set and the analysis of cadmium pollution migration rules specifically include: Based on big data retrieval, cadmium pollution migration examples under different environments and different electric fields are obtained to form a cadmium pollution migration example data set, and cadmium pollution migration characteristics under each electric field state are extracted to obtain the first characteristic information; Performing migration rule analysis according to the first characteristic information, and constructing corresponding migration change trend graphs based on the migration characteristics under different electric fields; The migration change trend diagram constructed is used to calculate the migration change amount and change rate of cadmium pollution in different time periods under each electric field. The migration trend of cadmium pollution under different electric fields is analyzed as an analysis indicator to obtain migration trend analysis information. Perform abnormal migration detection according to the migration trend analysis information, judge the migration change amount of cadmium pollution in each time period with a preset threshold, analyze the abnormal change trend, and obtain abnormal migration detection information; Extracting the corresponding abnormal time period according to the abnormal migration detection information, extracting the corresponding electric field parameters through the first characteristic information and marking them, to obtain abnormal migration analysis information; The migration trend analysis information and the abnormal migration analysis information are combined to form the first analysis information.

9. The cadmium pollution migration law analysis system based on data analysis according to claim 7, characterized in that: The migration influencing factors analysis is performed based on the cadmium pollution migration example data set, and the influence degree of each influencing factor is evaluated, specifically including: Acquire a cadmium pollution migration example data set, extract environmental characteristics under each electric field according to the cadmium pollution migration example data set, and obtain second characteristic information; Acquire the first analysis information, perform migration influencing factor analysis in combination with the second feature information, and calculate the Mahalanobis distance between the second feature information and the first feature information based on the Mahalanobis distance algorithm as an influencing factor analysis indicator; The calculated Mahalanobis distance is compared with a preset threshold value, and the correlation between each environmental feature and the migration law of cadmium pollution under the corresponding electric field is analyzed according to the judgment result to obtain the correlation analysis information; Analyze the influencing factors that affect the migration law of cadmium pollution according to the correlation analysis information, calculate the ratio of the characteristics corresponding to each influencing factor to the total characteristics in combination with the second characteristic information, and construct a probability matrix; The entropy weight method is introduced to evaluate the degree of influence. The information entropy of each influencing factor is calculated according to the constructed probability matrix, and the difference coefficient is calculated through the information entropy of each influencing factor. The weight of each influencing factor is calculated based on the calculated difference coefficient, and the influence degree of each influencing factor on the migration law is analyzed according to the calculated weight to obtain the influence degree analysis information; The correlation analysis information and the influence degree analysis information are combined to form the second analysis information.

10. The cadmium pollution migration law analysis system based on data analysis according to claim 7, characterized in that: The combining of the first analysis information and the second analysis information to analyze the migration law of cadmium pollution under different electric fields and constructing a migration law analysis model specifically includes: Obtaining first analysis information and second analysis information, analyzing the migration law of cadmium pollution under different electric fields according to the first analysis information and the second analysis information, and constructing a migration law knowledge graph; A migration law analysis model was built based on the migration law knowledge graph and the cadmium pollution migration case data set, and the Markov algorithm was introduced to build the model; Constructing a state space according to the migration law knowledge graph, defining the migration state of cadmium pollution according to the migration laws under different environments and different electric fields, each migration state represents an independent migration law; The state transition probability is calculated based on the cadmium pollution migration instance data set, and the probability of each state in the state space transferring to the next state is calculated by analyzing the historical data in the cadmium pollution migration instance data set to obtain the state transition probability; Constructing a transition probability matrix according to the state transition probability, modifying the constructed transition probability matrix based on the expert analysis method, setting the initial state probability distribution, and constructing a migration law analysis model in combination with the state space and the transition probability matrix; A training data set is constructed based on the migration law knowledge graph and the cadmium pollution migration instance data set to perform deep learning and training on the migration law analysis model to obtain a migration law analysis model that meets the expectations.

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