Prediction of Water Quality Using Machine Learning

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Author(s): Tran Thi Hong Ngoc (An Giang University. Vietnam), Phan Truong Khanh (An Giang University, Vietnam)and Sabyasachi Pramanik (Haldia Institute of Technology, India)
Copyright: 2024
Pages: 20
Source title: Advanced Geospatial Practices in Natural Environment Resource Management
Source Author(s)/Editor(s): Rubeena Vohra (Bharati Vidyapeeth's College of Engineering, India)and Ashish Kumar (Bennett University, India)
DOI: 10.4018/979-8-3693-1396-1.ch004

Keywords: Environment & Agriculture / Geographic Information Systems / Information Science Reference / Natural Resource Management

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Abstract

With the fast growth of aquatic data, machine learning is essential for data analysis, categorization, and prediction. Data-driven models using machine learning may effectively handle complicated nonlinear problems in water research, unlike conventional approaches. Machine learning models and findings have been used to build, monitor, simulate, evaluate, and optimize water treatment and management systems in water environment research. Machine learning may also enhance water quality, pollution control, and watershed ecosystem security. This chapter discusses how ML approaches were used to assess water quality in surface, ground, drinking, sewage, and ocean. The authors also suggest potential machine learning applications in aquatic situations.

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