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Determination of the unit hydrograph of a typical urban basin using genetic programming and artificial neural networks
Author(s) -
Rabuñal J. R.,
Puertas J.,
Suárez J.,
Rivero D.
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.6250
Subject(s) - hydrograph , genetic programming , artificial neural network , computer science , genetic algorithm , structural basin , flow (mathematics) , surface runoff , hydrology (agriculture) , environmental science , artificial intelligence , machine learning , ecology , mathematics , geology , geotechnical engineering , paleontology , geometry , biology
An application of genetic programming (GP) and artificial neural networks (ANNs) in hydrology is proposed, showing how these two techniques can work together to solve the problem of modelling the effect of rain on the runoff flow in a typical urban basin. The ability of GP to include the physical basis of a problem and even to analyse the results is discussed, and a case study is included as an example. We propose a solution to this problem by using an ANN for the prediction of the daily flow due to human activity of the citizens and the use of GP for the prediction of the flow rate resulting from the rain. Finally, it is shown that the methodology can be used to solve similar problems by combining both techniques. Copyright © 2006 John Wiley & Sons, Ltd.