Abstract
Logic-based compatibility measures [97, 98] use the interpretation the membership function of a fuzzy set as indicating a degree of truth of a proposition represented by the fuzzy set (see Section 4.4). We will consider two methods for generating compatibility measures from a logical interpretation of membership. The first approach, which has been employed as a basis for inference in fuzzy rule-based expert systems, uses fuzzy truth values to represent the degree of compatibility between two fuzzy sets. The second approach defines an elementwise degree of equality between membership functions of two fuzzy sets.
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© 2002 Springer-Verlag Berlin Heidelberg
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Cross, V.V., Sudkamp, T.A. (2002). Logic-Based Measures. In: Similarity and Compatibility in Fuzzy Set Theory. Studies in Fuzziness and Soft Computing, vol 93. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1793-5_9
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DOI: https://doi.org/10.1007/978-3-7908-1793-5_9
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-2507-7
Online ISBN: 978-3-7908-1793-5
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