توضیحات
ABSTRACT
This paper proposes a genetic-algorithm-based approach to the construction of fuzzy classification systems with
rectangular fuzzy rules. In the proposed approach, compact fuzzy classification systems are automatically constructed from numerical data by selecting a small number of significant fuzzy rules using genetic algorithms. Since significant fuzzy rules are selected and unnecessary fuzzy rules are removed, the proposed approach can be viewed as a knowledge acquisition tool for classification problems. In this paper, we first describe a generation method of rectangular fuzzy rules from numerical data for classification problems. We next formulate a rule selection problem for constructing a compact fuzzy classification system as a combinatorial optimization problem with two objectives: to minimize the number of selected fuzzy rules and to maximize the number of correctly classified patterns. We then show how genetic algorithms are applied to the rule selection problem. Last, we illustrate the proposed approach by computer simulations on numerical examples and the iris data of Fisher.
INTRODUCTION
Fuzzy-rule-based control systems have been applied to various problem (for example, see [14, 18]). Fuzzyrules in those control systems were usually derived from human experts. Recently several approaches have been proposed for automatically generating fuzzy rules from numerical data without domain experts
[19, 21,24].Tuning techniques for the membership functions of antecedent and consequent fuzzy sets have been also proposed in many studies. For example, Ichihashi and Watanabe [6-1 and Nomura et al. [16] proposed tuning techniques based on descent methods. Horikawa et al. [5], Jang [11-1 and Lin and Lee 1-15] combined the learning ability of neural networks with fuzzy control systems to form self-learning fuzzy controllers.
Year : 1994
Publisher : ELSEVIER
By : Hisao Ishibuchi, Ken Nozaki, Naohisa Yamamoto, Hideo Tanaka
File Information : English Language / 17 Page / Size : 910 KB
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سال : 1994
ناشر : ELSEVIER
کاری از : Hisao Ishibuchi, Ken Nozaki, Naohisa Yamamoto, Hideo Tanaka
اطلاعات فایل : زبان انگلیسی / 17 صفحه / حجم : 910 کیلو بایت
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