Water Quality Modelling of River Periyar Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System

Abstract Water is requisite on earth for life to survive. The study area of the present work river Periyar, longest in Kerala, India. overall objective compare accuracy and performance artificial neural network (ANN) adaptive neuro-fuzzy inference system (ANFIS) training prediction dissolved oxygen (DO) concentration biochemical demand (BOD) river. models were used examine secondary data from past four water quality metrics generated at five monitoring stations located along Periyar predict DO concentrations BOD. was examined using root mean square error (RMSE) coefficient correlation (R) values. This revealed that ANN superior ANFIS most scenarios. In situations, appears get superiority training, however, seemed have dominant position testing validation. inputs having highest relevance case identified be nitrate phosphate concentrations, whereas total solids COD seen impactful BOD forecasting employing sensitivity analysis.