Cluster-based self-organizing neuro-fuzzy system with hybrid learning approach for function approximation

Chunshien Li, Kuo Hsiang Cheng, Chih Ming Chen, Jin Long Chen

研究成果: 雜誌貢獻會議論文同行評審

摘要

A novel hybrid cluster-based self-organizing neuro-fuzzy system (HC-SONFS) is proposed for dynamic function approximation and prediction. With the mechanism of self-organization, fuzzy rules are generated in the form of clusters using the proposed self-organization method to achieve compact and sufficient system structure if the current structure of knowledge base is insufficient to satisfy the required performance. A hybrid learning algorithm combining the well-known random optimization (RO) and the least square estimation (LSE) is use for fast learning. An example of chaos time series for system identification and prediction is illustrated. Compared to other approaches, excellent performance of the proposed HC-SONFS is observed.

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頁(從 - 到)1186-1189
頁數4
期刊Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
3612
發行號PART III
DOIs
出版狀態已出版 - 2005
事件First International Conference on Natural Computation, ICNC 2005 - Changsha, China
持續時間: 27 8月 200529 8月 2005

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