Non-linear water level forecasting of Dungun river using hybridization of backpropagation neural network and genetic algorithm
The Department of Irrigation and Drainage (DID) and Meteorological Malaysia Department (MMD) have identified that water level is one of the important indicators for flooding control. The aim of this study is to find the best regression model and to identify the dominant variables of water level in D...
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Format: | Thesis |
Language: | English |
Published: |
2014
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Online Access: | http://eprints.utm.my/50690/25/SitiHajarArbainMFC2014.pdf |