2026-04-13T04:09:22Zhttps://recercat.cat/oai/requestoai:recercat.cat:2117/1654002025-07-17T02:46:00Zcom_2072_1033col_2072_452950
Hybrid evolutionary data analysis technique for environmental modeling
Acosta, Jesus
Nebot Castells, M. Àngela
Fuertes Armengol, José Mª
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica
Evolutionary computation
Genetic algorithms
Air -- Pollution -- Mathematical models
Ozone forecast
Environmental modeling
Evolutionary algorithms
Fuzzy inductive reasoning
Genetic fuzzy systems
Computació evolutiva
Algorismes genètics
Aire -- Contaminació -- Models matemàtics
In this work an evolutionary fuzzy system (EFS) is presented and applied to an environmental problem, i.e. modeling ozone concentrations. The hybrid system is composed by a FIR methodology and a genetic algorithm (GA) that take charge of determining, in an automatic way, the fuzzification parameters in that fuzzy system. The obtained results are compared with some of the most popular and classical modeling methods, neural networks and other FIR models.
Peer Reviewed
Postprint (published version)
2006
Conference report
Open Access
International Centre for Numerical Methods in Engineering (CIMNE)