River water quality prediction using adaptive Neuro-fuzzy inference system and artificial neural network modeling: a review

Nur Najwa Mohd Rizal, . and Hayder, Gasim (2020) River water quality prediction using adaptive Neuro-fuzzy inference system and artificial neural network modeling: a review. Journal of Energy and Environment (Malaysia), 12 (2). pp. 1-7. ISSN 1985-7462

Water is the source of life and rivers, the main source of water are vital for all aspects of ecosystems and also, for human health. In order to control the water quality environment more accurately, artificial intelligence (AI) is applied to increase the preciseness of the water quality prediction. The implementation of AI viz. adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) in predicting river water quality parameters is quite new in the whole wide world but it is slowly replacing the traditional techniques in forecasting the major parameters of surface waters. Although the classical methods still can be used but it may not give outputs and results that are more accurate than the ANN and ANFIS. Therefore, this paper is a review aimed at how ANN and ANFIS can improve in evaluate the river water quality than the traditional techniques used before.

Full text available from: Official URL: https://journal.uniten.edu.my/index.php/jee/articl...

Abstract

Water is the source of life and rivers, the main source of water are vital for all aspects of ecosystems and also, for human health. In order to control the water quality environment more accurately, artificial intelligence (AI) is applied to increase the preciseness of the water quality prediction. The implementation of AI viz. adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) in predicting river water quality parameters is quite new in the whole wide world but it is slowly replacing the traditional techniques in forecasting the major parameters of surface waters. Although the classical methods still can be used but it may not give outputs and results that are more accurate than the ANN and ANFIS. Therefore, this paper is a review aimed at how ANN and ANFIS can improve in evaluate the river water quality than the traditional techniques used before.

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Item Type:	Article
AGROVOC Term:	river water
AGROVOC Term:	water pollution
AGROVOC Term:	water quality
AGROVOC Term:	water resources
AGROVOC Term:	data analysis
AGROVOC Term:	hydrology
AGROVOC Term:	water management
AGROVOC Term:	environmental monitoring
Geographical Term:	Malaysia
Depositing User:	Nor Hasnita Abdul Samat
Date Deposited:	20 Nov 2025 09:32
Last Modified:	20 Nov 2025 09:32
URI:	http://webagris.upm.edu.my/id/eprint/1551

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