Artificial neural networks for rainfall runoff modelling with special reference to Sg. Bedup catchment area

Kuok, King Kuok (2004) Artificial neural networks for rainfall runoff modelling with special reference to Sg. Bedup catchment area. Masters thesis, Universiti Malaysia Sarawak (UNIMAS).

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Abstract

Artificial Neural Network (ANN) is an information-processing system composed of many nonlinear and densely interconnected processing elements or neurons. ANN is able to extract the relation between the inputs and outputs of a process, without the physics being explicitly provided to them. The natural behavior of hydrological processes is appropriate for the application ANN in hydrology. A rainfall runoff model for Sungai Bedup Basin in Sarawak was built using three different ANN architectures namely Multilayer perceptron (MLP), Recurrent (REC) and Radial Basic function (RBF).

Item Type: Thesis (Masters)
Additional Information: Thesis (M.Sc.) - Universiti Malaysia Sarawak, 2004.
Uncontrolled Keywords: UNIMAS, Universiti Malaysia Sarawak, research, postgraduate, engineering, Artificial Neural Network (ANN), university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, IPTA, education
Subjects: T Technology > TC Hydraulic engineering. Ocean engineering
Divisions: Academic Faculties, Institutes and Centres > Faculty of Engineering
Depositing User: Karen Kornalius
Date Deposited: 10 Jun 2014 02:13
Last Modified: 09 Mar 2020 00:47
URI: http://ir.unimas.my/id/eprint/3137

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