The Dynamic Detection of Water Quality Monitoring and Pollution Prevention and Control

Abstract

Abstract With the development of society, the material living standard of our people has been significantly improved, but we sacrificed the environment in the course of development, which led to the current number of environmental problems in our country is particularly large, so that now we need to pick up the tone of protecting the environment, so now the overall tone of the country is to protect the environment, adhere to the green water green mountain is the basic strategy of Jinshan Yinshan, play a good pollution prevention and control of the three major battles, care for the environment, protect the environment. And in the environment water is the most important, it carries everything, the purpose of this paper is to study based on water quality monitoring and pollution prevention and control of dynamic detection technology. In order to conduct the experiment better, after consulting the literature on water quality monitoring and pollution prevention and control, and dynamic detection technology, we used a variety of algorithms to construct a corresponding dynamic detection technology system to monitor water quality and conduct real-time surveys of pollutants, and obtain relevant experimental data to complete the experiment. The experimental results show that the improved adaptive parameter DBSCAN clustering algorithm is better than the AdaBoost algorithm and the genetic algorithm, so we finally choose to build a dynamic detection technology system using the improved adaptive parameter DBSCAN clustering algorithm.