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Fuzzy sets, fuzzy clustering and fuzzy rules in AI

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Book cover Fuzzy Logic in Artificial Intelligence (FLAI 1993)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 847))

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Abstract

We discuss the use of fuzzy set theory and semantic unification for fuzzy clustering and the use of fuzzy rules in knowlege bases. The paper provides a unification with probability theory and probabilistic fuzzy rules are discussed. Fuzzy sets are used to provide generalisation in clustering and pattern recognition methods.

Professor J. F. Baldwin is a SERC Senior Research Fellow

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References

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Authors and Affiliations

  1. Engineering Mathematics Department, University of Bristol, England

    J. F. Baldwin

Authors
  1. J. F. Baldwin
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Anca L. Ralescu

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© 1994 Springer-Verlag Berlin Heidelberg

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Baldwin, J.F. (1994). Fuzzy sets, fuzzy clustering and fuzzy rules in AI. In: Ralescu, A.L. (eds) Fuzzy Logic in Artificial Intelligence. FLAI 1993. Lecture Notes in Computer Science, vol 847. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58409-9_2

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  • DOI: https://doi.org/10.1007/3-540-58409-9_2

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58409-4

  • Online ISBN: 978-3-540-48780-7

  • eBook Packages: Springer Book Archive

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