Paper Title :Artificial Neural Network Model to Prediction Water Quality in Saen Saep Canal
Author :S. Ketchaya
Article Citation :S. Ketchaya ,
(2017 ) " Artificial Neural Network Model to Prediction Water Quality in Saen Saep Canal " ,
International Journal of Advances in Science, Engineering and Technology(IJASEAT) ,
pp. 40-44,
Volume-5, Issue-3, Spl. Iss-2
Abstract : Water quality is a subject of ongoing concern. Deterioration of water quality has initiated serious management
efforts in many countries. This study endeavors to automatically classify water quality. The water quality classes are
evaluated using 6 factor indices. These factors are pH value (pH), Dissolved Oxygen (DO), Biochemical Oxygen Demand
(BOD), Nitrate Nitrogen (NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (T-Coliform). The methodology involves
applying data mining techniques using multilayer perceptron (MLP) neural network models. The data consisted of 11 sites
of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage Bangkok
Metropolitan Administration during 2011-2015. The results of multilayer perceptron neural network exhibit a high
accuracy multilayer perception rate at 94.23% in classifying the water quality of Saen Saep canal in Bangkok
Subsequently, this encouraging result could be applied with plan and management source of water quality.
Keywords - Artificial neural network, prediction, water quality
Type : Research paper
Published : Volume-5, Issue-3, Spl. Iss-2
DOIONLINE NO - IJASEAT-IRAJ-DOIONLINE-9133
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Copyright: © Institute of Research and Journals
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Published on 2017-11-22 |
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