Fuzzy system design by a ga-based method for data classification

淡江大學機構典藏 > 工學院 > 電機工程學系暨研究所 > 期刊論文 > Item 987654321/46355

請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/46355

題名:	Fuzzy system design by a ga-based method for data classification
作者:	翁慶昌;Wong, Ching-chang;Lin, Bo-chen;Chen, Chia-chong
貢獻者:	淡江大學電機工程學系
日期:	2002-04
上傳時間:	2010-03-26 22:06:34 (UTC+8)
出版者:	Taylor & Francis
摘要:	In this paper, a method based on the Genetic Algorithm (GA) and SVD-QR method is proposed to construct an appropriate fuzzy system for data classification. In this method, an individual of the population in the GA is used to determine a fuzzy partition such that some rough fuzzy sets of each input variable are obtained. In order to extract significant fuzzy rules from the rule base of the defined fuzzy system, the SVD-QR method is applied to remove unnecessary fuzzy rules such that the constructed fuzzy system has a low number of fuzzy rules. A fitness function in the GA is considered to guide the search procedure to select an appropriate fuzzy system such that the number of correctly classified patterns are maximized and the number of fuzzy rules is minimized. Finally, a classification problem is considered to illustrate the effectiveness of the proposed method.
關聯:	Cybernetics and Systems 33(3), pp.253-270
DOI:	10.1080/019697202753551639
顯示於類別:	[電機工程學系暨研究所] 期刊論文

文件中的檔案:

檔案	大小	格式	瀏覽次數
	0Kb	Unknown	380	檢視/開啟

在機構典藏中所有的資料項目都受到原著作權保護.

TAIR相關文章