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Title of Journal: Soft Comput

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Abbravation: Soft Computing

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Springer-Verlag

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10.1002/sat.1024

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1433-7479

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An approach to fuzzy default reasoning for functio

Authors: Hisao Ishibuchi Takashi Yamamoto Tomoharu Nakashima
Publish Date: 2005/10/13
Volume: 10, Issue: 9, Pages: 850-
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Abstract

This paper discusses fuzzy reasoning for approximately realizing nonlinear functions by a small number of fuzzy ifthen rules with different specificity levels Our fuzzy rule base is a mixture of general and specific rules which overlap with each other in the input space General rules work as default rules in our fuzzy rule base First we briefly describe existing approaches to the handling of default rules in the framework of possibility theory Next we show that standard interpolationbased fuzzy reasoning leads to counterintuitive results when general rules include specific rules with different consequents Then we demonstrate that intuitively acceptable results are obtained from a nonstandard inclusionbased fuzzy reasoning method Our approach is based on the preference for more specific rules which is a commonly used idea in the field of default reasoning When a general rule includes a specific rule and they are both compatible with an input vector the weight of the general rule is discounted in fuzzy reasoning We also discuss the case where general rules do not perfectly but partially include specific rules Then we propose a geneticsbased machine learning GBML algorithm for extracting a small number of fuzzy ifthen rules with different specificity levels from numerical data using our inclusionbased fuzzy reasoning method Finally we describe how our approach can be applied to the approximate realization of fuzzy numbervalued nonlinear functions

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