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Water Pollution Prevention and Control Project, 2022, 3(1); doi: 10.38007/WPPCP.2022.030103.

Water Pollution Prevention and Control System Based on Cluster Analysis

Author(s)

Yongfeng Shi

Corresponding Author:
Yongfeng Shi
Affiliation(s)

China Water & Power Press, Beijing 100043, China

Abstract

At present, many developing areas will have low utilization rate of water resources and serious groundwater pollution (water pollution, WP), which makes the groundwater environment situation increasingly serious. In order to curb the trend of ground WP and improve the quality of groundwater environment, it is urgent to formulate a ground WP prevention and control plan. Many researchers have provided new ideas for the application research of WP prevention and control system. This paper is based on this as the research direction and research basis. This paper analyzes the significance of WP prevention and summarizes the application of WP prevention and control system and cluster analysis in WP prevention and control. This paper then establishes an algorithm model, and proposes relevant algorithms to provide theoretical basis for the application research of WP prevention and control system based on cluster analysis. At the end of the paper, the simulation experiment is carried out, and the experiment is summarized and discussed. According to the establishment of WP prevention and control systems in A and B, the growth rate of sewage from agricultural pollution sources from 2018 to 2022 is 29.5%. It can be inferred from the amount of sewage from agricultural pollution sources that this area is an industrial developed area. At the same time, with the in-depth study of fusion cluster analysis, the application research of WP control system is also facing new opportunities and challenges.

Keywords

Water Pollution, Prevention and Control System, Fusion Cluster Analysis, Pollution Sources

Cite This Paper

Yongfeng Shi. Water Pollution Prevention and Control System Based on Cluster Analysis. Water Pollution Prevention and Control Project (2022), Vol. 3, Issue 1: 22-31. https://doi.org/10.38007/WPPCP.2022.030103.

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