期刊論文
| 學年 | 90 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2002-04-01 |
| 作品名稱 | Fuzzy system design by a ga-based method for data classification |
| 作品名稱（其他語言） | |
| 著者 | 翁慶昌; Wong, Ching-chang; Lin, Bo-chen; Chen, Chia-chong |
| 單位 | 淡江大學電機工程學系 |
| 出版者 | Taylor & Francis |
| 著錄名稱、卷期、頁數 | Cybernetics and Systems 33(3), pp.253-270 |
| 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. |
| 關鍵字 | |
| 語言 | en_US |
| ISSN | 0196-9722 |
| 期刊性質 | 國外 |
| 收錄於 | |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | USA |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/46355 ) |