Open AccessWater quality control of Tasik Kejuruteraan UKM water channel using Artificial Neural Network and Neural Fuzzy Network
Author(s) -
Nazri Nor,
Muhammad Fuad,
Norhan Abd Rahman
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/991/1/012138
Subject(s) - environmental science , artificial neural network , water quality , channel (broadcasting) , quality (philosophy) , computer science , machine learning , ecology , biology , computer network , philosophy , epistemology
The water quality of Tasik Kejuruteraan UKM water channel is an issue that should be emphasized because excess water will be discharged to Sungai Langat where this river is the source of water supply for the residents in some part of Klang Valley area. The water quality parameters must comply with the standard assigned by Malaysian’s Department of Environment (DOE). As a first step towards proper monitoring programme, a proper analysis of the water quality should be conducted thoroughly. As such, this study composed of two parts. First, experimental investigation of the water quality of Tasik Kejuruteraan UKM water channel was carried out to assess its environmental quality. Experiment was conducted to determine the Water Quality Index of Tasik Kejuruteraan water channel based upon guidelines as stipulated by DOE. The results indicate that Tasik Kejuruteraan UKM water channel is polluted and proper water quality control should be applied. In the second part of this study, preliminary analysis of artificial neural network (ANN) and neural fuzzy network for water quality control was conducted to determine the suitability of these controllers in water treatment system. Based on the simulations conducted, neural fuzzy network shows better efficacy in the pH control scheme compared with ANN because there is no oscillation detected in the corresponding controlled variable.