Machine learning techniques in river water quality modelling: a research travelogue

被引:32
作者
Khullar, Sakshi [1 ]
Singh, Nanhey [2 ]
机构
[1] Guru Gobind Singh Indraprastha Univ, M-54,2nd Floor West Patel Nagar, New Delhi 110008, India
[2] AIACTR, CSE, GGSIPU, New Delhi 110031, India
关键词
machine learning; river water quality; water quality evaluation; water quality prediction; NEURAL-NETWORKS; PREDICTION; REGRESSION; TRENDS; INDEX;
D O I
10.2166/ws.2020.277
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Water is a prime necessity for the survival and sustenance of all living beings. Over the past few years, the water quality of rivers has been adversely affected due to harmful wastes and pollutants. This ever-increasing water pollution is a matter of great concern as it is deteriorating the water quality, making it unfit for any type of use. Contaminated water resources can cause serious effects on humans as well as aquatic life. Hence, water quality monitoring of reservoirs is essential. Recently, water quality modelling using AI techniques has generated a lot of interest and it can be very beneficial in ecological and water resources management. This paper presents the state-of-the-art application of machine learning techniques in forecasting river water quality. It highlights the different key techniques, advantages, disadvantages, and applications with respect to monitoring the river water quality. The review also intends to find the existing challenges and opportunities for future research.
引用
收藏
页码:1 / 13
页数:13
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