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Rainfall runoff modeling using radial basis function neural network for sungai Tinjar catchment, Miri, Sarawak

This study is to purposefully develop a rainfall runoff model for Sg. Tinjar with outlet at Long Jegan using Radial Basis Function (RBF) Neural Network. Training and simulation was done using MatLab 6.5.1 software with varying parameters to obtain the optimum result.

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Bibliographic Details
Main Authors: Suhaimi, S., Razali, I.
Format: E-Article
Language:English
English
Published: Universiti Malaysia Sarawak, (UNIMAS) 2009
Subjects:
GE Environmental Sciences
TD Environmental technology. Sanitary engineering
Online Access:http://ir.unimas.my/id/eprint/3115/1/Rainfall%20runoff%20modeling%20using%20radial%20basis%20function%20neural%20network%20for%20sungai%20Tinjar%20catchment%2C%20Miri%2C%20Sarawak.pdf
http://ir.unimas.my/id/eprint/3115/7/RAINFALL%20RUNOFF%20MODELING%20USING%20RADIAL%20BASIS%20FUNCTION%20NEURAL%20NETWORK%20FOR%20SUNGAI%20TINJAR%20CATCHMENT%2C%20MIRI%2C%20SARAWAK%20%28full%20text%29.pdf
http://ir.unimas.my/id/eprint/3115/
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http://ir.unimas.my/id/eprint/3115/1/Rainfall%20runoff%20modeling%20using%20radial%20basis%20function%20neural%20network%20for%20sungai%20Tinjar%20catchment%2C%20Miri%2C%20Sarawak.pdf
http://ir.unimas.my/id/eprint/3115/7/RAINFALL%20RUNOFF%20MODELING%20USING%20RADIAL%20BASIS%20FUNCTION%20NEURAL%20NETWORK%20FOR%20SUNGAI%20TINJAR%20CATCHMENT%2C%20MIRI%2C%20SARAWAK%20%28full%20text%29.pdf
http://ir.unimas.my/id/eprint/3115/

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