Artificial Neural Network for Daily Water Level Estimation
Rosmina Ahmad Bustami, and Nabil Bessaih, and Mohd Saufee Muhammad, (2006) Artificial Neural Network for Daily Water Level Estimation. Engineering e-Transaction, 1 (1). pp. 7-12. ISSN 1823-6379
Official URL: http://ejum.fsktm.um.edu.my/ArticleInformation.aspx?ArticleID=344
Universiti Malaysia Sarawak, Faculty of Engineering
A method for estimating water level at Sungai Bedup in Sarawak is presented here. The method makes use of Artificial Neural Network (ANN) – a new tool that is capable of modeling various nonlinear hydrological processes. ANN was chosen based on its ability to generalize patterns in imprecise or noisy and ambiguous input and output data sets. In this study, the networks were developed to forecast daily water level for Sungai Bedup station. Specially designed networks were simulated using data obtained from Drainage and Irrigation Department with MATLAB 6.5 computer software. Various training parameters were considered to achieve the best result. ANN Recurrent Network using Backpropagation algorithm was adopted for this study.
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