Civil and Environmental Science Journal
Vol 1, No 1 (2018)

Application of Artificial Neural Network For Defining The Water Quality in The River


Haribowo, Riyanto, Dermawan, Very, Yudha, Nevandria Satrya



Article Info

Publish Date
20 Mar 2018

Abstract

Predicting point and nonpoint source runoff of dissolved and suspended materials into their receiving streams is important to protecting water quality. Therefore, it is important to monitoring the condition of river water quality. The purpose of this study is to predict water quality in small streams using an Artificial Neural Network (ANN). The study focuses on small stream in tributary of Brantas River. The variables of interest are dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), pH and temperature (T). To validate the performance of the trained ANN, it was applied to an unseen data set from a station in the region. The result show that the prediction of DO is 6.03 mg/litre, pH is 6,47 mg/litre and temperature is 25.18°. With the relatively error was 15.63%, 12.64% and 14.12% respectively. It was finally concluded that ANN models are capable of simulating the water quality parameters.


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Original Source : http://civense.ub.ac.id/index.php/civense/article/view/6
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Journal Info

Abbrev

civense

Publisher

Subject

Civil Engineering, Building, Construction & Architecture Engineering Environmental Science

Description

Civil and Environmental Science Journal (CIVENSE) is an international journal, peer-reviewed research publication covering new concepts, theories, methods, and techniques related to science and engineering. ...