期刊論文
| 學年 | 95 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2007-03-01 |
| 作品名稱 | Hybrid Recursive Particle Swarm Optimization Learning Algorithm in the Design of Radial Basis Function Networks |
| 作品名稱（其他語言） | |
| 著者 | Feng, Hsuan-ming; Chen, Ching-yi; 余繁; Ye, Fun |
| 單位 | 淡江大學電機工程學系 |
| 出版者 | Springer |
| 著錄名稱、卷期、頁數 | Journal of Marine Science and Technology 15(1), pp.31-40 |
| 摘要 | In this paper, an innovative hybrid recursive particle swarm optimization (HRPSO) learning algorithm with normalized fuzzy c-mean (NFCM) clustering, particle swarm optimization (PSO) and recursive least-squares (RLS) is proposed to generate radial basis function networks (RBFNs) modeling system with small numbers of descriptive radial basis functions (RBFs) for fast approximating two complex and nonlinear functions. Simulation results demonstrate that the generated NFCM-based learning schemes approach the desired modeling systems within the smaller population sizes. |
| 關鍵字 | normalized fuzzy c-means; particle swarm optimization; recursive least-squares; radial basis function networks |
| 語言 | en |
| ISSN | 0948-4280 |
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| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/50550 ) |