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Predicting rainfall intensity using a genetic algorithm approach
Author(s) -
Karahan Halil,
Ceylan Halim,
Tamer Ayvaz M.
Publication year - 2006
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.6245
Subject(s) - intensity (physics) , transformation (genetics) , genetic algorithm , mean squared error , return period , mathematics , algorithm , computer science , statistics , mathematical optimization , physics , geography , biochemistry , chemistry , quantum mechanics , gene , flood myth , archaeology
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 periods. Copyright © 2006 John Wiley & Sons, Ltd.