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 Faculties, Institutes, Centres > Faculty of Engineering |
| Depositing User: | Karen Kornalius |
| Date Deposited: | 10 Jun 2014 02:13 |
| Last Modified: | 20 Jun 2023 07:50 |
| URI: | http://ir.unimas.my/id/eprint/3137 |
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