Yu Yuan, Dazhi Xu
College of Economics and Management, Hunan University of Arts and Science, Changde, China
Due to the complexity of water pollution treatment and the impact of external factors, precise regulation of water pollution has always been one of the problems in the environmental field. Traditional methods cannot meet the increasingly complex engineering project requirements. Machine learning methods developed in recent years provide a series of effective solutions for such problems. Taking the Xiangjiang River basin as an example, this paper introduces the characteristics of machine learning methods such as artificial neural network, support vector machine and random forest, and expounds the application of machine learning methods in the field of water pollution control in the Xiangjiang River basin from three aspects of water quality prediction and early warning, fault diagnosis of sewage treatment system and intelligent control, and analyzes the advantages of machine learning methods compared with traditional methods and the problems existing in the application of machine learning methods in water pollution control in the Xiangjiang River basin, the prospect and trend of the application of machine learning methods in the field of water pollution control in the Xiangjiang River basin are forecasted.
machine learning, water pollution, intelligent control, governance, mechanism
Yu Yuan, Dazhi Xu. Research on the Water Pollution Control Mechanism of Xiangjiang River Basin Based on Machine Learning. Academic Journal of Environment & Earth Science (2022) Vol. 4 Issue 8: 48-52. https://doi.org/10.25236/AJEE.2022.040809.
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