Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/4327
Title: Predicting rainfall intensity using a genetic algorithm approach
Authors: Karahan, Halil
Ceylan, Halim.
Tamer Ayvaz, Mustafa
Keywords: Genetic algorithm
Parameter estimation
Rainfall intensity
Genetic algorithms
Mathematical models
Mathematical transformations
Mean square error
Rain
Genetic algorithm rainfall intensity (GARI) model
Rainfall intensity-duration-frequency relations
Weather forecasting
estimation method
genetic algorithm
parameterization
precipitation assessment
precipitation intensity
prediction
return period
Abstract: A genetic algorithm rainfall intensity (GARI) model has been developed and used to predict the intensities for given return period. It is a one-step solution procedure that may not require any mathematical transformation. The problem formulation is given and the genetic algorithm solution of the problem is presented. The results show that the proposed GARI model can be used to solve the rainfall intensity-duration-frequency relations with lowest mean-squared error between measured and predicted intensities. Predicted intensities are in good agreement between measured and predicted values for given return period. Copyright © 2006 John Wiley & Sons, Ltd.
URI: https://hdl.handle.net/11499/4327
https://doi.org/10.1002/hyp.6245
ISSN: 0885-6087
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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