New Results on Fuzzy Regression by Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{golubski:2002:EuroGP,

• title = "New Results on Fuzzy Regression by Using Genetic Programming",
• author = "Wolfgang Golubski",
• editor = "James A. Foster and Evelyne Lutton and Julian Miller and Conor Ryan and Andrea G. B. Tettamanzi",
• booktitle = "Genetic Programming, Proceedings of the 5th European Conference, EuroGP 2002",
• volume = "2278",
• series = "LNCS",
• pages = "308--315",
• publisher = "Springer-Verlag",
• address = "Kinsale, Ireland",
• publisher_address = "Berlin",
• month = "3-5 " # apr,
• year = "2002",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-43378-3",
• DOI = "doi:10.1007/3-540-45984-7_30",
• abstract = "In this paper we continue the work on symbolic fuzzy regression problems. That means that we are interesting in finding a fuzzy function f with best matches k given data pairs (x,y) of fuzzy numbers. We use a genetic programming approach for finding a suitable fuzzy function and will present test results about linear, quadratic and cubic fuzzy functions.",
• notes = "EuroGP'2002, part of \cite{lutton:2002:GP}",

}

Genetic Programming entries for Wolfgang Golubski

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