Publicacións

@article{Rabuñal2007476,

title = {Determination of the unit hydrograph of a typical urban basin using genetic programming and artificial neural networks},

author = {Juan R. Rabuñal-Dopico and Jerónimo Puertas-Agudo and Joaquín Suárez-López and Daniel Rivero},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33847065032&doi=10.1002%2fhyp.6250&partnerID=40&md5=3e33b99eff05c3ca9229c7c35745f145},

doi = {10.1002/hyp.6250},

issn = {08856087},

year  = {2007},

date = {2007-01-01},

urldate = {2007-01-01},

journal = {Hydrological Processes},

volume = {21},

number = {4},

pages = {476-485},

abstract = {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.},

note = {cited By 68},

keywords = {artificial intelligence; artificial neural network; genetic algorithm; hydrograph; rainfall-runoff modeling; urban drainage, Artificial intelligence; Catchments; Computer simulation; Genetic algorithms; Genetic programming; Hydrology; Neural networks; Runoff, Artificial intelligence; Catchments; Computer simulation; Genetic algorithms; Genetic programming; Neural networks; Runoff, Hydrology, Unit hydrograph; Urban basin; Water runoff transformation},

pubstate = {published},

tppubtype = {article}

}