Automatic Generation of Fuzzy Classification Systems Using Hyper-Cone Membership Functions

Material type: その他

Author: HNG, Linaほか

Publisher: IEEE

Publication date: 2003

Material Format: Digital

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Note (General)：: 出版タイプ： AOIn this paper, we propose automatic generation methods of fuzzy classification rules with the Genetic Algorithms (GAs) to obtain compact fuzz...

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Material Type: その他
Title: Automatic Generation of Fuzzy Classification Systems Using Hyper-Cone Membership Functions
Author/Editor: HNG, Lina
INOUE, Hiroyuki
MIYASAKA, Kenji
TSUKAMOTO, Mitsuru
Author Heading: HNG, Lina
INOUE, Hiroyuki
MIYASAKA, Kenji
TSUKAMOTO, Mitsuru
Publication, Distribution, etc.: IEEE
Publication Date: 2003
Publication Date (W3CDTF): 2003
Periodical title: Proc. of 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation
No. or year of volume/issue: 2
Volume: 2
Pages: 658-663
Subject Heading: Fuzzy Classification System
Hyper-cone Membership Function
Genetic Algorithms
Target Audience: 一般
Note (General): 出版タイプ： AO
In this paper, we propose automatic generation methods of fuzzy classification rules with the Genetic Algorithms (GAs) to obtain compact fuzzy systems. This time, we propose an approach of hyper-cone membership function to construct rules for the antecedent part. Then, this method is determined the location and shape of hyper-cone membership function in the antecedent part, output class and the number of necessary inputs of each rule by GAs. Also, using the rule addition method in GA process, compact fuzzy classification systems are obtained. Though the proposed methods are quite simple, the process of GAs on both methods presents a solving for two-objective optimization problems: increasing the numbers of correct pattern classification, while decreasing the rule and input numbers optimally. This method was applied to Wine data sets and Wisconsin Prognostic Breast Cancer (WPBC) data sets. Wine data sets consist of 13 inputs and three outputs, while WPBC data sets contain 33 inputs and two outputs.
Data Provider (Database): 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）
https://irdb.nii.ac.jp
Original Data Provider (Database): 福井大学 : 福井大学学術機関リポジトリ