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Water Pollution Prevention and Control Project, 2023, 4(1); doi: 10.38007/WPPCP.2023.040106.

Genetic Algorithm of GIS in Water Pollution Control Planning


Cioara Tudor

Corresponding Author:
Cioara Tudor

Newcastle Univ, Framlington Pl, Newcastle Upon Tyne NE2 4HH, Tyne & Wear, England


Water is the source of life. The shortage of water resources and environmental pollution have become the bottleneck restricting economic development. The main pollutants are organic substances, such as sewage nitrogen, biochemical oxygen demand, permanganate index, volatile phenol, etc. These factors affect a wide range of areas and have a high degree of harm. In order to make full use of water resources and reduce water pollution (WP for short here), it is necessary to treat water environment as a whole to make it meet the water quality standards. In this paper, GIS (Geographic Information Science) technology is used for comprehensive evaluation of water quality, and certain mathematical calculation methods are used to achieve quantitative and objective evaluation of water quality, so as to achieve the objective evaluation of water quality and work efficiency. Genetic algorithm (GA) is an adaptive global optimal probability search method, which imitates the genetic and evolutionary process of organisms in nature. In this paper, from the perspective of biological genetics, a GA for directly coding parameters is designed, which solves the problem that traditional nonlinear problems are easy to fall into local optimum. At present, it has been widely used in many aspects. Based on GA of GIS, this paper applies it to WP control planning. The study found that the cost of WP control system based on GA based on GIS was reduced by 30.32 million compared with the cost of WP control before improvement.


Water Pollution Control, Genetic Algorithm, Geographic Information System, Control Planning Model

Cite This Paper

Cioara Tudor. Genetic Algorithm of GIS in Water Pollution Control Planning. Water Pollution Prevention and Control Project (2023), Vol. 4, Issue 1: 48-57. https://doi.org/10.38007/WPPCP.2023.040106.


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