GIS在水污染控制规划中的遗传算法

Cioara Tudor
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摘要

水是生命之源。水资源短缺和环境污染已成为制约经济发展的瓶颈。主要污染物为有机物,如污水氮、生化需氧量、高锰酸盐指数、挥发性苯酚等。这些因素影响范围广,危害程度高。为了充分利用水资源,减少水污染(这里简称为WP),需要将水环境作为一个整体来对待,使其达到水质标准。本文采用GIS(地理信息科学)技术对水质进行综合评价,并采用一定的数学计算方法对水质进行定量、客观的评价,从而实现对水质的客观评价和工作效率的提高。遗传算法是一种模拟自然界生物遗传进化过程的自适应全局最优概率搜索方法。本文从生物遗传学的角度出发,设计了一种直接编码参数的遗传算法,解决了传统非线性问题容易陷入局部最优的问题。目前,它已经在许多方面得到了广泛的应用。本文基于GIS中的遗传算法,将其应用于WP控制规划中。研究发现,基于GIS的GA的WP控制系统成本比改进前的WP控制成本降低了3032万。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic Algorithm of GIS in Water Pollution Control Planning
: 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.
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