| Application of neural networks incorporated with real-valued genetic algorithms in knowledge acquisition | |
|---|---|
| 學年 | 88 |
| 學期 | 2 |
| 出版（發表）日期 | 2000-05-01 |
| 作品名稱 | Application of neural networks incorporated with real-valued genetic algorithms in knowledge acquisition |
| 作品名稱（其他語言） | |
| 著者 | 蘇木春; Su, Mu-chun; Chang, Hsiao-te |
| 單位 | 淡江大學電機工程學系 |
| 出版者 | Elsevier |
| 著錄名稱、卷期、頁數 | Fuzzy sets and systems 112(1), pp.85-97 |
| 摘要 | Often a major difficulty in the design of rule-based systems is the process of acquiring the requisite knowledge in the form of If–Then rules. This paper presents a class of fuzzy degraded hyperellipsoidal composite neural networks (FDHECNNs) that are trained to provide appealing solutions to the problem of knowledge acquisition. The values of the network parameters, after sufficient training, are then utilized to generate If–Then rules on the basis of preselected meaningful features. In order to avoid the risk of getting stuck in local minima during the training process, a real-valued genetic algorithm is proposed to train FDHECNNs. The effectiveness of the method is demonstrated on two problems, namely, the “truck backer-upper” problem as well as real-world application of a hypothesis regarding the pathophysiology of diabetes. |
| 關鍵字 | Neural networks; Pattern recognition; Medicine; Fuzzy control |
| 語言 | en |
| ISSN | 0165-0114 |
| 期刊性質 | 國內 |
| 收錄於 | |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | TWN |
| 公開徵稿 | |
| 出版型式 | ,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/46192 ) |
GoogleAnalytics