Neural network for rainfall runoff modelling

Hafiz Fadillah, Alhadi (2004) Neural network for rainfall runoff modelling. [E-LPTA] (Unpublished)

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Neural network is a very useful data modelling tool that is able to capture and represent complex input and output relationships. The advantage of neural network lies in its ability to represent both linear and non-linear relationships and also its ability to learn these relationships directly from the data being modelled. So, the purpose of this study is to develop a rainfall runoff model for Sungai Tinjar with outlet at Long Jegan, The network was trained using Back Propagation Algorithm.

Item Type: E-LPTA
Additional Information: Project report (BSc.) - Universiti Malaysia Sarawak, 2004.
Uncontrolled Keywords: UNIMAS, Universiti Malaysia Sarawak, engineering, research, undergraduate, neural network, Back Propagation Algorithm, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, IPTA, education
Subjects: Q Science > Q Science (General)
T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Engineering
Depositing User: Karen Kornalius
Date Deposited: 22 May 2014 01:19
Last Modified: 20 Aug 2015 08:22

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