| A clustering-based method for fuzzy modeling | |
|---|---|
| 學年 | 87 |
| 學期 | 2 |
| 出版（發表）日期 | 1999-06-01 |
| 作品名稱 | A clustering-based method for fuzzy modeling |
| 作品名稱（其他語言） | |
| 著者 | 翁慶昌; Wong, Ching-chang; Chen, Chia-chong |
| 單位 | 淡江大學電機工程學系 |
| 出版者 | Institute of Electronics, Information and Communication Engineers (IEICE) |
| 著錄名稱、卷期、頁數 | IEICE transactions on information and systems E82-D(6), pp.1058-1065 |
| 摘要 | In this paper, a clustering-based method is proposed for automatically constructing a multi-input Takagi-Sugeno (TS) fuzzy model where only the input-output data of the identified system are available. The TS fuzzy model is automatically generated by the process of structure identification and parameter identification. In the structure identification step, a clustering method is proposed to provide a systematic procedure to partition the input space so that the number of fuzzy rules and the shapes of fuzzy sets in the premise part are determined from the given input-output data. In the parameter identification step, the recursive least-squares algorithm is applied to choose the parameter values in the consequent part from the given input-output data. Finally, two examples are used to illustrate the effectiveness of the proposed method. |
| 關鍵字 | |
| 語言 | en |
| ISSN | 0916-8532 |
| 期刊性質 | 國外 |
| 收錄於 | |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | JPN |
| 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/987654321/46421 ) |
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