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International Conference on Artificial Intelligence: Methodology, Systems, and Applications

AIMSA 2000: Artificial Intelligence: Methodology, Systems, and Applications pp 283–291Cite as

Construction of Efficient Rulesets from Fuzzy Data through Simulated Annealing

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1904))

Abstract

This paper proposes a simulated annealing-based approach for obtaining compact efficient classification systems from fuzzy data. Different methods for generating decision rules from fuzzy data share a problem in multidimensional spaces: their high cardinality. In order to solve it, the method of simulated annealing is proposed. This approach is illustrated with two well-known learning sets.

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Authors and Affiliations

  1. Departamento de Matemática Aplicada, Universidad de Vigo, Campus A Xunqueira, 36005, Pontevedra, Spain

    Francisco Botana

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  1. Francisco Botana
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© 2000 Springer-Verlag Berlin Heidelberg

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Botana, F. (2000). Construction of Efficient Rulesets from Fuzzy Data through Simulated Annealing. In: Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2000. Lecture Notes in Computer Science, vol 1904. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45331-8_27

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  • DOI: https://doi.org/10.1007/3-540-45331-8_27

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41044-7

  • Online ISBN: 978-3-540-45331-4

  • eBook Packages: Springer Book Archive

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