CN116776183A - Hexavalent chromium pollution site identification and evaluation method and system - Google Patents
Hexavalent chromium pollution site identification and evaluation method and system Download PDFInfo
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Abstract
The invention relates to a hexavalent chromium pollution site identification and evaluation method and system, which belong to the technical field of pollution identification and evaluation. According to the method, the clustered sample data is evaluated by the similarity measurement method integrating the PCA algorithm and the regular angle, so that the clustered sample data is corrected according to the evaluation result, and the classification precision of the polluted sample data can be improved.
Description
Technical Field
The invention relates to the technical field of pollution identification and evaluation, in particular to a hexavalent chromium pollution site identification and evaluation method and system.
Background
Hexavalent chromium is widely used in industrial and agricultural activities such as leather tanning, metallurgy, electroplating, ceramic glaze, wood preservation, etc., and hexavalent chromium slag and liquid waste generated by these industries are the main sources of hexavalent chromium pollution. In addition, hexavalent chromium contained in fertilizers (phosphate fertilizers, biosolids, etc.) can also cause hexavalent chromium pollution of agricultural soil. Hexavalent chromium can inhibit nitrification of organic matters in soil, has adverse effects on absorption and accumulation of plant nutrient elements, causes serious wilting of plant tops, and has obvious inhibition effect on plant growth. Hexavalent chromium also affects the mitosis of root tip cells, and the root system has extremely strong enrichment effect on hexavalent chromium, so that plant roots decay and fall off to finally die. Hexavalent chromium can enter animals and human bodies through food chains, affects oxidation, reduction and hydrolysis processes, can denature proteins, precipitates nucleic acids and nucleoproteins, interferes with an enzyme system, and causes dysfunction of red blood cells in carrying oxygen after the hexavalent chromium enters blood. For the identification process of hexavalent chromium pollution, the processes of data acquisition, data processing and data identification are required, and for the processes of data processing and data identification of massive data after the processes of data acquisition, the processes of rapid identification and evaluation of a pollution site are required to be identified by using related algorithms, and fuzzy clustering algorithms are generated; however, the fuzzy clustering algorithm at present is easy to fall into a local optimal solution due to the selection problem of the number of the clustering centers, so that the phenomenon of wrong classification of part of sample data is caused, and the recognition and evaluation accuracy of a polluted site are not high.
Disclosure of Invention
The invention overcomes the defects of the prior art and provides a hexavalent chromium pollution site identification and evaluation method and system.
In order to achieve the above purpose, the invention adopts the following technical scheme:
the invention provides a hexavalent chromium pollution site identification and evaluation method, which comprises the following steps:
acquiring pollution sample data information acquired by each hexavalent chromium pollution site, and preprocessing the pollution sample data information acquired by each hexavalent chromium pollution site to acquire preprocessed pollution sample data information;
introducing a fuzzy clustering algorithm, and clustering the preprocessed pollution sample data information according to the fuzzy clustering algorithm to obtain a membership matrix of the preprocessed pollution sample data information;
introducing a similarity measurement method of a regular angle, and correcting the membership matrix of the preprocessed pollution sample data information by the similarity measurement method of the regular angle to obtain a membership matrix of the corrected pollution sample data information;
and acquiring a hexavalent chromium pollution distribution map of the target area according to the membership matrix of the corrected pollution sample data information, and generating a final soil restoration scheme based on the hexavalent chromium pollution distribution map of the target area.
Further, in the method, the pollution sample data information collected by each hexavalent chromium pollution site is preprocessed, so that the preprocessed pollution sample data information is obtained, and the method specifically comprises the following steps:
constructing a pollution sample data aggregation density distribution map of each hexavalent chromium pollution site according to pollution sample data information acquired by each hexavalent chromium pollution site, and introducing a local outlier detection algorithm;
local outlier factor values of each sample data in a pollution sample data aggregation density distribution map of each hexavalent chromium pollution site are collected through a local outlier detection algorithm, and local outlier factor threshold information is preset;
judging whether the local outlier factor value is larger than the local outlier factor threshold information, and eliminating sample data with the local outlier factor value larger than the local outlier factor threshold information when the local outlier factor value is larger than the local outlier factor threshold information;
when the local outlier factor value is not greater than the local outlier factor threshold information, the sample data of which the local outlier factor value is not greater than the local outlier factor threshold information is used as final sample data, and the final sample data is used as preprocessed pollution sample data information to be output.
Further, in the method, a fuzzy clustering algorithm is introduced, and the clustering processing is carried out on the preprocessed pollution sample data information according to the fuzzy clustering algorithm, so as to obtain a membership matrix of the preprocessed pollution sample data information, which specifically comprises the following steps:
introducing a fuzzy clustering algorithm, initializing the number of clustering centers, calculating the Euclidean distance from each preprocessed pollution sample data information to each clustering center, and selecting the clustering center corresponding to the minimum Euclidean distance as the clustering center of each preprocessed pollution sample data information;
acquiring the Euclidean distance of each piece of current preprocessed pollution sample data information according to a clustering center of each piece of preprocessed pollution sample data information, setting average Euclidean distance threshold information, and counting the Euclidean distance of each piece of current preprocessed pollution sample data information to generate a total Euclidean distance;
calculating the average Euclidean distance of the polluted sample data according to the total Euclidean distance, introducing a genetic algorithm, setting a genetic algebra through the genetic algorithm, and judging whether the average Euclidean distance of the polluted sample data is larger than the average Euclidean distance threshold value information;
when the average Euclidean distance of the polluted sample data is larger than the average Euclidean distance threshold value information, carrying out iterative operation on the number of clustering centers until the average Euclidean distance of the polluted sample data is not larger than the average Euclidean distance threshold value information, acquiring the pollution membership corresponding to the preprocessed polluted sample data information, and constructing a membership matrix of the preprocessed polluted sample data information according to the corresponding pollution membership.
Further, in the method, a similarity measurement method of a regular angle is introduced, and the membership matrix of the preprocessed polluted sample data information is corrected by the similarity measurement method of the regular angle, so as to obtain the membership matrix of the corrected polluted sample data information, and the method specifically comprises the following steps:
introducing a PCA algorithm, decomposing a membership matrix of the preprocessed polluted sample data information through the PCA algorithm, generating an orthogonal matrix formed by characteristic vectors according to columns, and constructing an N-dimensional subspace according to the orthogonal matrix formed by the characteristic vectors according to the columns by taking each clustering center as a reference point;
acquiring feature vector information of an N-dimensional subspace, introducing a similarity measurement method of a regular angle, selecting a feature vector with highest occurrence frequency as a comparison vector, calculating the information of a regular angle cosine value between the comparison vector and the information of the rest feature vectors through the similarity measurement method of the regular angle, and setting a related regular angle cosine threshold;
if the regular angle cosine value information is larger than the relevant regular angle cosine threshold, acquiring sample data corresponding to the regular angle cosine value information larger than the relevant regular angle cosine threshold, and calculating the mahalanobis distance from the sample data corresponding to the regular angle cosine value information larger than the relevant regular angle cosine threshold to the sample data of other clustering centers;
And selecting a class cluster corresponding to the minimum Markov distance as a class cluster of sample data corresponding to which the regular angle cosine value information is larger than the relevant regular angle cosine threshold value, and generating a membership matrix of the modified polluted sample data information.
Further, in the method, a hexavalent chromium pollution distribution map of the target area is obtained according to the membership matrix of the corrected pollution sample data information, and the method specifically comprises the following steps:
obtaining pollution membership information of each hexavalent chromium pollution site in the target area according to the membership matrix of the corrected pollution sample data information, and obtaining digital terrain model data of the target area;
acquiring pollution membership information of hexavalent chromium in a three-dimensional direction according to pollution membership information of each hexavalent chromium pollution site in a target area, and acquiring a mapping relation between the pollution membership information of hexavalent chromium in the three-dimensional direction and digital terrain model data of the target area;
setting related rendering colors according to pollution membership information of hexavalent chromium in the three-dimensional direction, and generating a hexavalent chromium pollution distribution map of the target area based on the related rendering colors and the mapping relation between the pollution membership information of hexavalent chromium in the three-dimensional direction and digital terrain model data of the target area.
Further, in the method, a final soil remediation scheme is generated based on the hexavalent chromium pollution distribution map of the target area, and specifically comprises the following steps:
constructing a time stamp, acquiring migration data information of pollution of each hexavalent chromium pollution site in the three-dimensional direction according to a hexavalent chromium pollution distribution map of the target area, and calculating migration rate information within preset time by combining the time stamp and the migration data information;
constructing a migration rate sorting table, inputting migration rate information within a preset time into the migration rate sorting table for sorting, generating a migration rate sorting result, and generating soil restoration priority according to the migration rate sorting result;
acquiring a hexavalent chromium pollution restoration scheme through big data, constructing a soil restoration knowledge graph, introducing an attention mechanism to calculate the attention score of the hexavalent chromium pollution restoration scheme, merging the hexavalent chromium pollution restoration schemes with the same attention score, and generating a hexavalent chromium pollution restoration scheme based on attention score sequencing;
sequentially inputting hexavalent chromium pollution restoration schemes based on attention score ordering into different spaces of a soil restoration knowledge graph for storage, acquiring the hexavalent chromium pollution restoration scheme of the current pollution site according to the soil restoration knowledge graph, and generating a final soil restoration scheme based on the hexavalent chromium pollution restoration scheme of the current pollution site and the soil restoration priority.
The second aspect of the present invention provides a hexavalent chromium pollution site identification and evaluation system, the system including a memory and a processor, the memory including a hexavalent chromium pollution site identification and evaluation method program, the hexavalent chromium pollution site identification and evaluation method program implementing the following steps when executed by the processor:
acquiring pollution sample data information acquired by each hexavalent chromium pollution site, and preprocessing the pollution sample data information acquired by each hexavalent chromium pollution site to acquire preprocessed pollution sample data information;
introducing a fuzzy clustering algorithm, and clustering the preprocessed pollution sample data information according to the fuzzy clustering algorithm to obtain a membership matrix of the preprocessed pollution sample data information;
introducing a similarity measurement method of a regular angle, and correcting the membership matrix of the preprocessed pollution sample data information by the similarity measurement method of the regular angle to obtain a membership matrix of the corrected pollution sample data information;
and acquiring a hexavalent chromium pollution distribution map of the target area according to the membership matrix of the corrected pollution sample data information, and generating a final soil restoration scheme based on the hexavalent chromium pollution distribution map of the target area.
Further, in the system, a fuzzy clustering algorithm is introduced, and the clustering processing is performed on the preprocessed pollution sample data information according to the fuzzy clustering algorithm, so as to obtain a membership matrix of the preprocessed pollution sample data information, which specifically comprises the following steps:
introducing a fuzzy clustering algorithm, initializing the number of clustering centers, calculating the Euclidean distance from each preprocessed pollution sample data information to each clustering center, and selecting the clustering center corresponding to the minimum Euclidean distance as the clustering center of each preprocessed pollution sample data information;
acquiring the Euclidean distance of each piece of current preprocessed pollution sample data information according to a clustering center of each piece of preprocessed pollution sample data information, setting average Euclidean distance threshold information, and counting the Euclidean distance of each piece of current preprocessed pollution sample data information to generate a total Euclidean distance;
calculating the average Euclidean distance of the polluted sample data according to the total Euclidean distance, introducing a genetic algorithm, setting a genetic algebra through the genetic algorithm, and judging whether the average Euclidean distance of the polluted sample data is larger than the average Euclidean distance threshold value information;
when the average Euclidean distance of the polluted sample data is larger than the average Euclidean distance threshold value information, carrying out iterative operation on the number of clustering centers until the average Euclidean distance of the polluted sample data is not larger than the average Euclidean distance threshold value information, acquiring the pollution membership corresponding to the preprocessed polluted sample data information, and constructing a membership matrix of the preprocessed polluted sample data information according to the corresponding pollution membership.
Further, in the system, a similarity measurement method of a regular angle is introduced, and the membership matrix of the preprocessed polluted sample data information is corrected by the similarity measurement method of the regular angle, so that the membership matrix of the corrected polluted sample data information is obtained, and the method specifically comprises the following steps:
introducing a PCA algorithm, decomposing a membership matrix of the preprocessed polluted sample data information through the PCA algorithm, generating an orthogonal matrix formed by characteristic vectors according to columns, and constructing an N-dimensional subspace according to the orthogonal matrix formed by the characteristic vectors according to the columns by taking each clustering center as a reference point;
acquiring feature vector information of an N-dimensional subspace, introducing a similarity measurement method of a regular angle, selecting a feature vector with highest occurrence frequency as a comparison vector, calculating the information of a regular angle cosine value between the comparison vector and the information of the rest feature vectors through the similarity measurement method of the regular angle, and setting a related regular angle cosine threshold;
if the regular angle cosine value information is larger than the relevant regular angle cosine threshold, acquiring sample data corresponding to the regular angle cosine value information larger than the relevant regular angle cosine threshold, and calculating the mahalanobis distance from the sample data corresponding to the regular angle cosine value information larger than the relevant regular angle cosine threshold to the sample data of other clustering centers;
And selecting a class cluster corresponding to the minimum Markov distance as a class cluster of sample data corresponding to which the regular angle cosine value information is larger than the relevant regular angle cosine threshold value, and generating a membership matrix of the modified polluted sample data information.
A third aspect of the present invention provides a computer-readable storage medium including a hexavalent chromium pollution site identification and evaluation method program, which when executed by a processor, implements the steps of any one of the hexavalent chromium pollution site identification and evaluation methods.
The invention solves the defects existing in the background technology, and has the following beneficial effects:
according to the invention, the pollution sample data information acquired by each hexavalent chromium pollution site is acquired, the pollution sample data information acquired by each hexavalent chromium pollution site is preprocessed, the preprocessed pollution sample data information is acquired, a fuzzy clustering algorithm is introduced, the preprocessed pollution sample data information is clustered according to the fuzzy clustering algorithm, the membership matrix of the preprocessed pollution sample data information is acquired, a similarity measurement method of a regular angle is introduced, the membership matrix of the preprocessed pollution sample data information is corrected according to the similarity measurement method of the regular angle, the membership matrix of the corrected pollution sample data information is acquired, finally, the hexavalent chromium pollution distribution map of a target area is acquired according to the membership matrix of the corrected pollution sample data information, and a final soil restoration scheme is generated based on the hexavalent chromium pollution distribution map of the target area. According to the method, the clustered sample data is evaluated by the similarity measurement method integrating the PCA algorithm and the regular angle, so that the clustered sample data is corrected according to the evaluation result, and the classification precision of the polluted sample data can be improved. On the other hand, the number of clustering centers is iteratively selected by introducing a genetic algorithm, so that the clustering precision of the polluted sample data can be improved, and the polluted sample data can be classified rapidly.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other embodiments of the drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 shows an overall process flow diagram of a hexavalent chromium contaminated site identification and assessment method;
FIG. 2 shows a first method flow chart of a hexavalent chromium contaminated site identification and assessment method;
FIG. 3 shows a second method flow chart of a hexavalent chromium contaminated site identification and assessment method;
fig. 4 shows a system block diagram of a hexavalent chromium pollution site identification and evaluation system.
Detailed Description
In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present application and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
As shown in fig. 1, the first aspect of the present invention provides a hexavalent chromium pollution site identification and evaluation method, comprising the steps of:
s102, acquiring pollution sample data information acquired by each hexavalent chromium pollution site, and preprocessing the pollution sample data information acquired by each hexavalent chromium pollution site to acquire preprocessed pollution sample data information;
in step S102, the method specifically includes:
constructing a pollution sample data aggregation density distribution map of each hexavalent chromium pollution site according to pollution sample data information acquired by each hexavalent chromium pollution site, and introducing a local outlier detection algorithm;
local outlier factor values of each sample data in a pollution sample data aggregation density distribution map of each hexavalent chromium pollution site are collected through a local outlier detection algorithm, and local outlier factor threshold information is preset;
judging whether the local outlier factor value is larger than the local outlier factor threshold information, and eliminating sample data with the local outlier factor value larger than the local outlier factor threshold information when the local outlier factor value is larger than the local outlier factor threshold information;
When the local outlier factor value is not greater than the local outlier factor threshold information, the sample data of which the local outlier factor value is not greater than the local outlier factor threshold information is used as final sample data, and the final sample data is used as preprocessed pollution sample data information to be output.
When the local outlier factor value is larger than the local outlier factor threshold value information, the data are outlier data, and the outlier data can be removed by the method, so that the cleaning of the pollution data is finished, and the evaluation accuracy of the pollution site is improved.
S104, introducing a fuzzy clustering algorithm, and clustering the preprocessed pollution sample data information according to the fuzzy clustering algorithm to obtain a membership matrix of the preprocessed pollution sample data information;
as shown in fig. 2, in step S104, the method specifically includes:
s202, introducing a fuzzy clustering algorithm, initializing the number of clustering centers, calculating the Euclidean distance from each preprocessed pollution sample data information to each clustering center, and selecting the clustering center corresponding to the minimum Euclidean distance as the clustering center of each preprocessed pollution sample data information;
s204, acquiring the Euclidean distance of each piece of current preprocessed pollution sample data information according to a clustering center of each piece of preprocessed pollution sample data information, setting average Euclidean distance threshold information, and counting the Euclidean distance of each piece of current preprocessed pollution sample data information to generate a total Euclidean distance;
S206, calculating the average Euclidean distance of the polluted sample data according to the total Euclidean distance, introducing a genetic algorithm, setting a genetic algebra through the genetic algorithm, and judging whether the average Euclidean distance of the polluted sample data is larger than the average Euclidean distance threshold value information;
and S208, when the average Euclidean distance of the polluted sample data is larger than the average Euclidean distance threshold value information, carrying out iterative operation on the number of clustering centers until the average Euclidean distance of the polluted sample data is not larger than the average Euclidean distance threshold value information, acquiring the pollution membership corresponding to the preprocessed polluted sample data information, and constructing a membership matrix of the preprocessed polluted sample data information according to the corresponding pollution membership.
The fuzzy clustering algorithm can be improved by the genetic algorithm, so that the number of clustering centers is adjusted, the classification precision of polluted sample data is improved, and the phenomenon of local optimal solution is avoided. The pollution membership degree corresponding to the pretreated pollution sample data information comprises low pollution, medium pollution, high pollution and the like.
S106, introducing a similarity measurement method of the regular angle, and correcting the membership matrix of the preprocessed pollution sample data information through the similarity measurement method of the regular angle to obtain the membership matrix of the corrected pollution sample data information;
As shown in fig. 3, in step S106, the method specifically includes:
s302, introducing a PCA algorithm, decomposing a membership matrix of the preprocessed polluted sample data information through the PCA algorithm, generating an orthogonal matrix formed by characteristic vectors according to columns, and constructing an N-dimensional subspace according to the orthogonal matrix formed by the characteristic vectors according to the columns by taking each clustering center as a reference point;
s304, acquiring feature vector information of an N-dimensional subspace, introducing a similarity measurement method of a regular angle, selecting a feature vector with highest occurrence frequency as a comparison vector, calculating the information of a regular angle cosine value between the comparison vector and the rest feature vector information through the similarity measurement method of the regular angle, and setting a related regular angle cosine threshold;
s306, if the regular angle cosine value information is larger than the relevant regular angle cosine threshold, acquiring sample data corresponding to the regular angle cosine value information larger than the relevant regular angle cosine threshold, and calculating the mahalanobis distance from the sample data corresponding to the regular angle cosine value information larger than the relevant regular angle cosine threshold to sample data of other clustering centers;
s308, selecting a class cluster corresponding to the minimum March distance as a class cluster of sample data corresponding to which the regular angle cosine value information is larger than the relevant regular angle cosine threshold value, and generating a membership matrix of the modified polluted sample data information.
It should be noted that, the regular angle cosine value information of the feature vector information corresponding to the sample data is obtained by introducing a PCA algorithm and a similarity measurement method of the regular angle, when the regular angle cosine value information is larger than the relevant regular angle cosine threshold value, the sample data with abnormal classification exists between the sample data, and the complexity of calculation is reduced by introducing the PCA algorithm, so as to form an N-dimensional subspace; and the similarity between the two subspaces is calculated through a similarity measurement method of the regular angle, so that the sample data is evaluated. The method can further correct the sample data, improves the clustering precision of the polluted sample data, and rapidly evaluates the pollution degree of the polluted sample data. Selecting a class cluster of sample data corresponding to the minimum mahalanobis distance as a class cluster of sample data corresponding to which the information of the regular angle cosine value is larger than the relevant regular angle cosine threshold value
S108, acquiring a hexavalent chromium pollution distribution map of the target area according to the membership matrix of the corrected pollution sample data information, and generating a final soil restoration scheme based on the hexavalent chromium pollution distribution map of the target area.
Further, in the method, a hexavalent chromium pollution distribution map of the target area is obtained according to the membership matrix of the corrected pollution sample data information, and the method specifically comprises the following steps:
Obtaining pollution membership information of each hexavalent chromium pollution site in the target area according to the membership matrix of the corrected pollution sample data information, and obtaining digital terrain model data of the target area;
acquiring pollution membership information of hexavalent chromium in a three-dimensional direction according to pollution membership information of each hexavalent chromium pollution site in a target area, and acquiring a mapping relation between the pollution membership information of hexavalent chromium in the three-dimensional direction and digital terrain model data of the target area;
setting related rendering colors according to pollution membership information of hexavalent chromium in the three-dimensional direction, and generating a hexavalent chromium pollution distribution map of the target area based on the related rendering colors and the mapping relation between the pollution membership information of hexavalent chromium in the three-dimensional direction and digital terrain model data of the target area.
It should be noted that the digital terrain model is an analog representation of the continuous ground using a plurality of selected coordinate points of known x, y, z in an arbitrary coordinate system, and the digital terrain model is a digital representation of the terrain surface morphology attribute information, and is a digital description with spatial position features and terrain attribute features. The method can be used for carrying out visual display on the pollution condition, and related rendering colors are set according to actual conditions, such as that the dark red color represents high pollution, the red color represents medium pollution, the light red color represents low pollution and the green color represents pollution.
Further, in the method, a final soil remediation scheme is generated based on the hexavalent chromium pollution distribution map of the target area, and specifically comprises the following steps:
constructing a time stamp, acquiring migration data information of pollution of each hexavalent chromium pollution site in the three-dimensional direction according to a hexavalent chromium pollution distribution map of the target area, and calculating migration rate information within preset time by combining the time stamp and the migration data information;
constructing a migration rate sorting table, inputting migration rate information within a preset time into the migration rate sorting table for sorting, generating a migration rate sorting result, and generating soil restoration priority according to the migration rate sorting result;
acquiring a hexavalent chromium pollution restoration scheme through big data, constructing a soil restoration knowledge graph, introducing an attention mechanism to calculate the attention score of the hexavalent chromium pollution restoration scheme, merging the hexavalent chromium pollution restoration schemes with the same attention score, and generating a hexavalent chromium pollution restoration scheme based on attention score sequencing;
sequentially inputting hexavalent chromium pollution restoration schemes based on attention score ordering into different spaces of a soil restoration knowledge graph for storage, acquiring the hexavalent chromium pollution restoration scheme of the current pollution site according to the soil restoration knowledge graph, and generating a final soil restoration scheme based on the hexavalent chromium pollution restoration scheme of the current pollution site and the soil restoration priority.
The method can set the soil restoration priority according to the migration rate of hexavalent chromium pollution, so that the restoration process of the soil pollution is more reasonable; secondly, the attention score of the hexavalent chromium pollution repairing scheme is calculated by introducing an attention mechanism, and the hexavalent chromium pollution repairing schemes with the same attention score are combined, which is equivalent to combining repairing schemes which are described differently and are substantially the same, and the hexavalent chromium pollution repairing schemes ordered based on the attention score are sequentially input into different spaces of the soil repairing knowledge graph for storage, so that the query speed of the hexavalent chromium pollution repairing scheme is improved.
In the invention, the clustered sample data is evaluated by the similarity measurement method of fusing the PCA algorithm and the regular angle, so that the clustered sample data is corrected according to the evaluation result, and the classification precision of the polluted sample data can be improved. On the other hand, the number of clustering centers is iteratively selected by introducing a genetic algorithm, so that the clustering precision of the polluted sample data can be improved, and the polluted sample data can be classified rapidly.
In addition, the invention can also comprise the following steps:
acquiring image data information of each hexavalent chromium pollution site in a target area through a remote sensing technology, and identifying plant types of the image data information of each hexavalent chromium pollution site in the target area to acquire plant type information living in each hexavalent chromium pollution site in the target area;
acquiring the absorption characteristic data information of each plant type on hexavalent chromium pollution through big data, constructing a database, and inputting the absorption characteristic data information of each plant type on hexavalent chromium pollution into the database for storage;
inputting plant type information living in each hexavalent chromium pollution site in the target area into the database for identification, and acquiring absorption characteristic data information corresponding to the plant type information living in each hexavalent chromium pollution site in the target area;
acquiring pollution concentration information corresponding to pollution membership of each hexavalent chromium pollution site and quantity information of each plant type in each pollution site, and calculating pollutant concentration data which can be absorbed by plants in each pollution site in each target area according to the quantity information of each plant type in each pollution site and absorption characteristic data information corresponding to plant type information living in each hexavalent chromium pollution site in the target area;
When the pollutant concentration data absorbed by the plants in the pollution site is greater than the pollution concentration information corresponding to the pollution membership of the hexavalent chromium pollution site, reducing the soil restoration grade of the current area, and simultaneously carrying out early warning on crops in the target area.
It should be noted that, in practice, the absorption characteristics of different plant species on hexavalent chromium are inconsistent, for example, the absorption capacity of horsebeans on hexavalent chromium is 0.42mg/kg, rape is 0.02 mg/kg, when the pollutant concentration data which can be absorbed by the plants in the pollution site is greater than the pollutant concentration information corresponding to the pollution membership of the hexavalent chromium pollution site, the site can complete self phytoremediation, at the moment, the soil remediation grade of the current area is treated, and meanwhile, crops in the target area are early warned, so that the rationality of a soil remediation scheme can be improved, and on the other hand, crops in the target area can be early warned in time.
In addition, the invention can also comprise the following steps:
acquiring pollution concentration data information and pollution area range information of each hexavalent chromium in a target area, and generating average pollution concentration information according to the pollution concentration data information and the pollution area range information of each hexavalent chromium in the target area;
Acquiring absorption characteristic data information corresponding to each plant type information through the database, and judging whether the corresponding absorption characteristic data information is larger than the average pollution concentration information or not;
when the corresponding absorption characteristic data information is larger than the average pollution concentration information, acquiring plant type information corresponding to the absorption characteristic data information larger than the average pollution concentration information;
and acquiring the corresponding plant cost data information of which the absorption characteristic data information is larger than the plant type information corresponding to the average pollution concentration information, sequencing according to the plant cost data information, and selecting the plant type information with the lowest plant cost as the most final plant restoration scheme for recommendation.
By the method, the plant repair scheme with the lowest planting cost and the most final plant species information can be selected for recommendation according to the actual pollution condition, so that the selection rationality of the repair scheme is improved.
The second aspect of the present invention provides a hexavalent chromium pollution site identification and evaluation system 4, the system 4 including a memory 41 and a processor 62, the memory 41 including a hexavalent chromium pollution site identification and evaluation method program, the hexavalent chromium pollution site identification and evaluation method program being executed by the processor 62 to implement the steps of:
Acquiring pollution sample data information acquired by each hexavalent chromium pollution site, and preprocessing the pollution sample data information acquired by each hexavalent chromium pollution site to acquire preprocessed pollution sample data information;
introducing a fuzzy clustering algorithm, and clustering the preprocessed pollution sample data information according to the fuzzy clustering algorithm to obtain a membership matrix of the preprocessed pollution sample data information;
introducing a similarity measurement method of a regular angle, and correcting the membership matrix of the preprocessed pollution sample data information by the similarity measurement method of the regular angle to obtain a membership matrix of the corrected pollution sample data information;
and acquiring a hexavalent chromium pollution distribution map of the target area according to the membership matrix of the corrected pollution sample data information, and generating a final soil restoration scheme based on the hexavalent chromium pollution distribution map of the target area.
Further, in the system, a fuzzy clustering algorithm is introduced, and the clustering processing is performed on the preprocessed pollution sample data information according to the fuzzy clustering algorithm, so as to obtain a membership matrix of the preprocessed pollution sample data information, which specifically comprises the following steps:
Introducing a fuzzy clustering algorithm, initializing the number of clustering centers, calculating the Euclidean distance from each preprocessed pollution sample data information to each clustering center, and selecting the clustering center corresponding to the minimum Euclidean distance as the clustering center of each preprocessed pollution sample data information;
acquiring the Euclidean distance of each piece of current preprocessed pollution sample data information according to a clustering center of each piece of preprocessed pollution sample data information, setting average Euclidean distance threshold information, and counting the Euclidean distance of each piece of current preprocessed pollution sample data information to generate a total Euclidean distance;
calculating the average Euclidean distance of the polluted sample data according to the total Euclidean distance, introducing a genetic algorithm, setting a genetic algebra through the genetic algorithm, and judging whether the average Euclidean distance of the polluted sample data is larger than the average Euclidean distance threshold value information;
when the average Euclidean distance of the polluted sample data is larger than the average Euclidean distance threshold value information, carrying out iterative operation on the number of clustering centers until the average Euclidean distance of the polluted sample data is not larger than the average Euclidean distance threshold value information, acquiring the pollution membership corresponding to the preprocessed polluted sample data information, and constructing a membership matrix of the preprocessed polluted sample data information according to the corresponding pollution membership.
Further, in the system, a similarity measurement method of a regular angle is introduced, and the membership matrix of the preprocessed polluted sample data information is corrected by the similarity measurement method of the regular angle, so that the membership matrix of the corrected polluted sample data information is obtained, and the method specifically comprises the following steps:
introducing a PCA algorithm, decomposing a membership matrix of the preprocessed polluted sample data information through the PCA algorithm, generating an orthogonal matrix formed by characteristic vectors according to columns, and constructing an N-dimensional subspace according to the orthogonal matrix formed by the characteristic vectors according to the columns by taking each clustering center as a reference point;
acquiring feature vector information of an N-dimensional subspace, introducing a similarity measurement method of a regular angle, selecting a feature vector with highest occurrence frequency as a comparison vector, calculating the information of a regular angle cosine value between the comparison vector and the information of the rest feature vectors through the similarity measurement method of the regular angle, and setting a related regular angle cosine threshold;
if the regular angle cosine value information is larger than the relevant regular angle cosine threshold, acquiring sample data corresponding to the regular angle cosine value information larger than the relevant regular angle cosine threshold, and calculating the mahalanobis distance from the sample data corresponding to the regular angle cosine value information larger than the relevant regular angle cosine threshold to the sample data of other clustering centers;
And selecting a class cluster corresponding to the minimum Markov distance as a class cluster of sample data corresponding to which the regular angle cosine value information is larger than the relevant regular angle cosine threshold value, and generating a membership matrix of the modified polluted sample data information.
A third aspect of the present application provides a computer-readable storage medium including a hexavalent chromium pollution site identification and evaluation method program, which when executed by a processor, implements the steps of any one of the hexavalent chromium pollution site identification and evaluation methods.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
The foregoing is merely illustrative embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think about variations or substitutions within the technical scope of the present invention, and the invention should be covered. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (10)
1. The hexavalent chromium pollution site identification and evaluation method is characterized by comprising the following steps of:
acquiring pollution sample data information acquired by each hexavalent chromium pollution site, and preprocessing the pollution sample data information acquired by each hexavalent chromium pollution site to acquire preprocessed pollution sample data information;
introducing a fuzzy clustering algorithm, and clustering the preprocessed pollution sample data information according to the fuzzy clustering algorithm to obtain a membership matrix of the preprocessed pollution sample data information;
introducing a similarity measurement method of a regular angle, and correcting the membership matrix of the preprocessed pollution sample data information by the similarity measurement method of the regular angle to obtain a membership matrix of the corrected pollution sample data information;
and acquiring a hexavalent chromium pollution distribution map of the target area according to the membership matrix of the corrected pollution sample data information, and generating a final soil restoration scheme based on the hexavalent chromium pollution distribution map of the target area.
2. The hexavalent chromium pollution site identification and evaluation method according to claim 1, wherein the pollution sample data information collected by each hexavalent chromium pollution site is preprocessed, and the preprocessed pollution sample data information is obtained, and specifically comprises the following steps:
Constructing a pollution sample data aggregation density distribution map of each hexavalent chromium pollution site according to the pollution sample data information collected by each hexavalent chromium pollution site, and introducing a local outlier detection algorithm;
local outlier factor values of each sample data in a pollution sample data aggregation density distribution map of each hexavalent chromium pollution site are subjected to the local outlier detection algorithm, and local outlier factor threshold information is preset;
judging whether the local outlier factor value is larger than the local outlier factor threshold information, and eliminating sample data of which the local outlier factor value is larger than the local outlier factor threshold information when the local outlier factor value is larger than the local outlier factor threshold information;
and when the local outlier factor value is not greater than the local outlier factor threshold information, taking the sample data of which the local outlier factor value is not greater than the local outlier factor threshold information as final sample data, and outputting the final sample data as preprocessed pollution sample data information.
3. The hexavalent chromium pollution site identification and evaluation method according to claim 1, wherein a fuzzy clustering algorithm is introduced, the pretreated pollution sample data information is clustered according to the fuzzy clustering algorithm, and a membership matrix of the pretreated pollution sample data information is obtained, and the method specifically comprises the following steps:
Introducing a fuzzy clustering algorithm, initializing the number of clustering centers, calculating the Euclidean distance from each preprocessed pollution sample data information to each clustering center, and selecting the clustering center corresponding to the minimum Euclidean distance as the clustering center of each preprocessed pollution sample data information;
acquiring the Euclidean distance of each piece of current preprocessed pollution sample data information according to the clustering center of each piece of preprocessed pollution sample data information, setting average Euclidean distance threshold information, and counting the Euclidean distance of each piece of current preprocessed pollution sample data information to generate total Euclidean distance;
calculating the average Euclidean distance of the polluted sample data according to the total Euclidean distance, introducing a genetic algorithm, setting a genetic algebra through the genetic algorithm, and judging whether the average Euclidean distance of the polluted sample data is larger than the average Euclidean distance threshold value information;
and when the average Euclidean distance of the pollution sample data is larger than the average Euclidean distance threshold value information, carrying out iterative operation on the number of the clustering centers until the average Euclidean distance of the pollution sample data is not larger than the average Euclidean distance threshold value information, acquiring the pollution membership corresponding to the preprocessed pollution sample data information, and constructing a membership matrix of the preprocessed pollution sample data information according to the corresponding pollution membership.
4. The hexavalent chromium pollution site identification and evaluation method according to claim 1, wherein a regular angle similarity measurement method is introduced, the membership matrix of the preprocessed pollution sample data information is corrected by the regular angle similarity measurement method, and the membership matrix of the corrected pollution sample data information is obtained, and specifically comprises the following steps:
introducing a PCA algorithm, decomposing the membership matrix of the preprocessed pollution sample data information through the PCA algorithm to generate an orthogonal matrix formed by characteristic vectors according to columns, and constructing an N-dimensional subspace according to the orthogonal matrix formed by the characteristic vectors according to the columns by taking each clustering center as a reference point;
acquiring feature vector information of the N-dimensional subspace, introducing a similarity measurement method of a regular angle, selecting a feature vector with highest occurrence frequency as a comparison vector, calculating the information of a regular angle cosine value between the comparison vector and the information of the rest feature vectors through the similarity measurement method of the regular angle, and setting a related regular angle cosine threshold;
if the regular angle cosine value information is larger than the relevant regular angle cosine threshold, acquiring sample data corresponding to the regular angle cosine value information larger than the relevant regular angle cosine threshold, and calculating the mahalanobis distance from the sample data corresponding to the regular angle cosine value information larger than the relevant regular angle cosine threshold to sample data of other clustering centers;
And selecting a class cluster corresponding to the minimum Markov distance as a class cluster of sample data corresponding to which the regular angle cosine value information is larger than the relevant regular angle cosine threshold value, and generating a membership matrix of the modified polluted sample data information.
5. The hexavalent chromium pollution site identification and evaluation method according to claim 1, wherein the hexavalent chromium pollution distribution map of the target area is obtained according to a membership matrix of the modified pollution sample data information, specifically comprising:
acquiring pollution membership information of each hexavalent chromium pollution site in the target area according to the membership matrix of the corrected pollution sample data information, and acquiring digital terrain model data of the target area;
acquiring pollution membership information of hexavalent chromium in a three-dimensional direction according to the pollution membership information of each hexavalent chromium pollution site in the target area, and acquiring a mapping relation between the pollution membership information of hexavalent chromium in the three-dimensional direction and digital terrain model data of the target area;
setting related rendering colors according to the pollution membership information of hexavalent chromium in the three-dimensional direction, and generating a hexavalent chromium pollution distribution map of the target area based on the related rendering colors and the mapping relation between the pollution membership information of hexavalent chromium in the three-dimensional direction and digital terrain model data of the target area.
6. The hexavalent chromium pollution site identification and evaluation method according to claim 1, characterized in that a final soil remediation scheme is generated based on the hexavalent chromium pollution profile of the target area, comprising the steps of:
constructing a time stamp, acquiring migration data information of pollution of each hexavalent chromium pollution site in the three-dimensional direction according to a hexavalent chromium pollution distribution map of the target area, and calculating migration rate information within preset time by combining the time stamp and the migration data information;
constructing a migration rate sorting table, inputting migration rate information within the preset time into the migration rate sorting table for sorting, generating a migration rate sorting result, and generating soil restoration priority according to the migration rate sorting result;
acquiring a hexavalent chromium pollution restoration scheme through big data, constructing a soil restoration knowledge graph, introducing an attention mechanism to calculate the attention score of the hexavalent chromium pollution restoration scheme, merging the hexavalent chromium pollution restoration schemes with the same attention score, and generating a hexavalent chromium pollution restoration scheme based on attention score sequencing;
sequentially inputting the hexavalent chromium pollution remediation schemes based on the attention score ranking into different spaces of the soil remediation knowledge graph for storage, acquiring the hexavalent chromium pollution remediation scheme of the current pollution site according to the soil remediation knowledge graph, and generating a final soil remediation scheme based on the hexavalent chromium pollution remediation scheme of the current pollution site and the soil remediation priority.
7. The hexavalent chromium pollution site identification and evaluation system is characterized by comprising a memory and a processor, wherein the memory comprises a hexavalent chromium pollution site identification and evaluation method program, and when the hexavalent chromium pollution site identification and evaluation method program is executed by the processor, the method comprises the following steps:
acquiring pollution sample data information acquired by each hexavalent chromium pollution site, and preprocessing the pollution sample data information acquired by each hexavalent chromium pollution site to acquire preprocessed pollution sample data information;
introducing a fuzzy clustering algorithm, and clustering the preprocessed pollution sample data information according to the fuzzy clustering algorithm to obtain a membership matrix of the preprocessed pollution sample data information;
introducing a similarity measurement method of a regular angle, and correcting the membership matrix of the preprocessed pollution sample data information by the similarity measurement method of the regular angle to obtain a membership matrix of the corrected pollution sample data information;
and acquiring a hexavalent chromium pollution distribution map of the target area according to the membership matrix of the corrected pollution sample data information, and generating a final soil restoration scheme based on the hexavalent chromium pollution distribution map of the target area.
8. The hexavalent chromium pollution site identification and evaluation system according to claim 7, wherein a fuzzy clustering algorithm is introduced, the preprocessed pollution sample data information is clustered according to the fuzzy clustering algorithm, and a membership matrix of the preprocessed pollution sample data information is obtained, and the system specifically comprises:
introducing a fuzzy clustering algorithm, initializing the number of clustering centers, calculating the Euclidean distance from each preprocessed pollution sample data information to each clustering center, and selecting the clustering center corresponding to the minimum Euclidean distance as the clustering center of each preprocessed pollution sample data information;
acquiring the Euclidean distance of each piece of current preprocessed pollution sample data information according to the clustering center of each piece of preprocessed pollution sample data information, setting average Euclidean distance threshold information, and counting the Euclidean distance of each piece of current preprocessed pollution sample data information to generate total Euclidean distance;
calculating the average Euclidean distance of the polluted sample data according to the total Euclidean distance, introducing a genetic algorithm, setting a genetic algebra through the genetic algorithm, and judging whether the average Euclidean distance of the polluted sample data is larger than the average Euclidean distance threshold value information;
And when the average Euclidean distance of the pollution sample data is larger than the average Euclidean distance threshold value information, carrying out iterative operation on the number of the clustering centers until the average Euclidean distance of the pollution sample data is not larger than the average Euclidean distance threshold value information, acquiring the pollution membership corresponding to the preprocessed pollution sample data information, and constructing a membership matrix of the preprocessed pollution sample data information according to the corresponding pollution membership.
9. The hexavalent chromium pollution site identification and evaluation system according to claim 7, wherein a regular angle similarity measurement method is introduced, the membership matrix of the preprocessed pollution sample data information is corrected by the regular angle similarity measurement method, and the membership matrix of the corrected pollution sample data information is obtained, and the method specifically comprises the following steps:
introducing a PCA algorithm, decomposing the membership matrix of the preprocessed pollution sample data information through the PCA algorithm to generate an orthogonal matrix formed by characteristic vectors according to columns, and constructing an N-dimensional subspace according to the orthogonal matrix formed by the characteristic vectors according to the columns by taking each clustering center as a reference point;
Acquiring feature vector information of the N-dimensional subspace, introducing a similarity measurement method of a regular angle, selecting a feature vector with highest occurrence frequency as a comparison vector, calculating the information of a regular angle cosine value between the comparison vector and the information of the rest feature vectors through the similarity measurement method of the regular angle, and setting a related regular angle cosine threshold;
if the regular angle cosine value information is larger than the relevant regular angle cosine threshold, acquiring sample data corresponding to the regular angle cosine value information larger than the relevant regular angle cosine threshold, and calculating the mahalanobis distance from the sample data corresponding to the regular angle cosine value information larger than the relevant regular angle cosine threshold to sample data of other clustering centers;
and selecting a class cluster corresponding to the minimum Markov distance as a class cluster of sample data corresponding to which the regular angle cosine value information is larger than the relevant regular angle cosine threshold value, and generating a membership matrix of the modified polluted sample data information.
10. A computer readable storage medium, characterized in that it comprises a hexavalent chromium pollution site identification and evaluation method program, which, when executed by a processor, implements the steps of a hexavalent chromium pollution site identification and evaluation method according to any one of claims 1-6.
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| CN117808024B (en) * | 2024-02-29 | 2024-05-07 | 深圳市捷通科技有限公司 | Reader-writer equipment management method and system based on self-adaptive regulation and control |
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