Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10349173 | Applied Soft Computing | 2005 | 15 Pages |
Abstract
When applying fuzzy systems for data analysis, their approximation and interpretation capabilities are two important aspects. Cascaded fuzzy system (CFS) is a new special class of hierarchical fuzzy systems in architectures proposed by Duan and Chung [IEEE Trans. Fuzzy Syst. 9 (2) (2001) 293] but its universal approximation capability is still not proved. When CFS is utilized in fuzzy data analysis/modeling, it seems very difficult to give a reasonable interpretation for intermediate variables and the corresponding fuzzy rules. A new cascaded centralized TSK fuzzy system (CCTSKFS) is presented in this paper, whose universal approximation capability is proved in detail, and what's more, we can interpret CCTSKFS more rationally. Finally, our experimental results demonstrate that CCTSKFS outperforms the classical cascaded TSK fuzzy system (CTSKFS) in approximation capability and robustness.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Shitong Wang, F.L. Chung, Shen HongBin, Hu Dewen,