New Results on Fuzzy Regression by Using Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{golubski:2002:EuroGP,
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title = "New Results on Fuzzy Regression by Using Genetic
Programming",
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author = "Wolfgang Golubski",
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editor = "James A. Foster and Evelyne Lutton and
Julian Miller and Conor Ryan and Andrea G. B. Tettamanzi",
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booktitle = "Genetic Programming, Proceedings of the 5th European
Conference, EuroGP 2002",
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volume = "2278",
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series = "LNCS",
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pages = "308--315",
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publisher = "Springer-Verlag",
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address = "Kinsale, Ireland",
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publisher_address = "Berlin",
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month = "3-5 " # apr,
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year = "2002",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "3-540-43378-3",
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DOI = "doi:10.1007/3-540-45984-7_30",
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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.",
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notes = "EuroGP'2002, part of \cite{lutton:2002:GP}",
- }
Genetic Programming entries for
Wolfgang Golubski
Citations