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Induction de règles floues interprétables

Abstract : This report deals with interpretable fuzzy rule induction from data for human-computer cooperation purposes. A review of fuzzy rule induction methods shows that they can be grouped into three families. Their comparison highlights the fact that the interpretability is not guaranteed. The central part of our work is a new fuzzy rule induction method. It aims to fulfill three interpretability conditions: readable fuzzy partitions, a number of rules as small as possible, incomplete rules. This is achieved through a three step procedure: generating a family of fuzzy partitions for each input variable, building an accurate fuzzy inference system, simplifying the rule base. The procedure is based on original concepts such as a metric distance suitable for fuzzy partitioning, and the input context defined by a set of rules. We introduced coverage and heterogeneity related indices to guide the prodedure, complementary with a numerical performance index. The method is first validated using well known data and then applied to decison making in a complex system. This application means to extract winemaking rules which enhance the color of red wine.
Keywords : thesis
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Submitted on : Thursday, May 14, 2020 - 8:23:47 PM
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  • HAL Id : tel-02580417, version 1
  • IRSTEA : PUB00010120



S. Guillaume. Induction de règles floues interprétables. Sciences de l'environnement. Doctorat, spécialité Systèmes informatiques, INSA Toulouse, 2001. Français. ⟨tel-02580417⟩



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