Publicacións

@article{Dorado2002190,

title = {Prediction and modelling of the flow of a typical urban basin through genetic programming},

author = {Julián Dorado and Juan R. Rabuñal-Dopico and Jerónimo Puertas-Agudo and Antonino Santos and Daniel Rivero},

editor = {Cagnoni S.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-44349112109&doi=10.1007%2f3-540-46004-7_20&partnerID=40&md5=1b562aeac3402bc60dc76a49a52901e6},

doi = {10.1007/3-540-46004-7_20},

issn = {03029743},

year  = {2002},

date = {2002-01-01},

urldate = {2002-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {2279 LNCS},

pages = {190-201},

publisher = {Springer Verlag},

abstract = {Genetic Programming (GP) is an evolutionary method that creates computer programs that represent approximate or exact solutions to a problem. This paper proposes an application of GP in hydrology, namely for modelling the effect of rain on the run-off flow in a typical urban basin. The ultimate goal of this research is to design a real time alarm system to warn of floods or subsidence in various types of urban basin. Results look promising and appear to offer some improvement over stochastic methods for analysing river basin systems such as unitary radiographs. © Springer-Verlag Berlin Heidelberg 2002.},

note = {cited By 14},

keywords = {Alarm systems; Combinatorial optimization; Genetic algorithms; Signal processing; Stochastic systems; Computer programming, Evolutionary method; Exact solution; Real-time alarm; River basins; Stochastic methods; Typical urban, Genetic programming},

pubstate = {published},

tppubtype = {article}

}