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Soil heavy metal enterprise pollution source recognition method based on source-sink spatial variable inference

A technology of spatial variables and identification methods, applied in character and pattern recognition, electrical digital data processing, special data processing applications, etc.

Active Publication Date: 2018-09-28
ZHEJIANG UNIV
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  • Summary
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  • Claims
  • Application Information

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Problems solved by technology

[0003] However, due to the existence of data islands, cross-departmental data cooperation is difficult, inter-departmental collaboration is difficult, and enterprise information acquisition is quite difficult

Method used

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  • Soil heavy metal enterprise pollution source recognition method based on source-sink spatial variable inference
  • Soil heavy metal enterprise pollution source recognition method based on source-sink spatial variable inference
  • Soil heavy metal enterprise pollution source recognition method based on source-sink spatial variable inference

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Embodiment

[0046] In the present embodiment, the above-mentioned method is used for analysis, and the specific steps are as follows:

[0047] Step 1) Data acquisition: Obtain the data of polluting enterprises in the research area, data of POI enterprises in the research area, topological data of administrative divisions in the research area, and soil heavy metal pollution data in the research area; for the data of polluting enterprises in the research area, its classification is required to comply with the national economic industry classification standard GB / T4752-2011; for the soil heavy metal pollution data in the study area, select the local soil survey data; for the POI enterprise data in the study area, the longitude and latitude information is required, and it belongs to the WGS84 coordinate system; in addition, the POI data is based on the Web API of Baidu map downloaded from;

[0048] Step 2) Enterprise data preprocessing: perform descriptive analysis on the polluting enterpris...

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Abstract

The invention discloses a soil heavy metal enterprise pollution source recognition method based on source-sink spatial variable inference. According to the method, first, pollution enterprise data, enterprise POI data and heavy metal pollution data in a to-be-studied region are acquired, enterprise industry category distribution of a dataset is adjusted, and a training dataset and a test dataset are separated after word segmentation processing is performed to eliminate local vocabularies; second, according to corpora established through the two datasets, the word frequency of words in all samples is subjected to statistical analysis to serve as text features corresponding to the samples, the samples of the training set are used to train a polynomial naive Bayesian model, and the model is assessed through scores of the test set; and last, industry categories and heavy metal pollution indexes are predicted according to the acquired enterprise data, numerical statistical analysis is performed in a grid generated according to the topological shape of the study region, a double-variable spatial self-correlation method is used to perform spatial analysis, the spatial distribution relation between pollution and enterprises is judged, and heavy metal point source and surface source pollution regions in the study region are recognized.

Description

technical field [0001] The invention relates to a method for identifying pollution sources of soil heavy metal enterprises based on reasoning of source-sink space variables, in particular to a classification method based on a specific text mining method and a bivariate spatial autocorrelation analysis method. technical background [0002] With the development of modern industrialization, some unregulated enterprises wantonly discharge industrial "three wastes", causing serious environmental pollution, among which soil heavy metal pollution has become a worldwide environmental problem. According to the survey, the total excess rate of soil pollution in the country is 16.1%. The main type of pollution is heavy metal pollution, which has caused damage to about 20 million hectares of farmland. Farmland soil pollution is mainly divided into point source pollution and non-point source pollution. Non-point source pollution refers to soil pollution caused by soil erosion and surface...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06F17/30G06K9/62
CPCG06F40/289G06F18/29G06F18/214
Inventor 史舟徐烨贾晓琳尤其浩
Owner ZHEJIANG UNIV
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