Parameter optimization methods for calibrating tank model and neural network for rainfall-runoff modelling
The transformation of rainfall into runoff involves many highly complex hydrological components that require various hydrological data and topographical information. These data are hard to obtain and not consistent. Therefore, hydrologic tank and artificial neural networks models that require only r...
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Format: | Thesis |
Language: | English |
Published: |
2010
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Online Access: | http://eprints.utm.my/id/eprint/36283/1/KuokKingKuokPFKA2010.pdf |
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