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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Cheng-Hung Chen Cheng-Jian Lin Chin-Teng Lin |
| Copyright Year | 2011 |
| Description | Author affiliation: Department of Electrical Engineering, National Chiao-Tung University, Hsinchu 300, Taiwan, R.O.C. (Chin-Teng Lin) || Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung County 411, Taiwan, R.O.C. (Cheng-Jian Lin) || Department of Electrical Engineering, National Formosa University Yunlin County 632, Taiwan, R.O.C. (Cheng-Hung Chen) |
| Abstract | This study presents an efficient immune symbiotic evolution learning algorithm for the compensatory neural fuzzy network (CNFN). The proposed immune symbiotic evolution learning method (ISEL) includes three major components — initial population, subgroup symbiotic evolution and immune system algorithm. The advantage of the proposed ISEL method are that the subgroup symbiotic evolution method uses the subgroup-based population to evaluate the fuzzy rules locally and the adopted immune system algorithm can accelerate the search and increase global search capacity. Finally, the simulation results have shown that the proposed CNFN-ISEL can outperform other methods. |
| Starting Page | 2819 |
| Ending Page | 2826 |
| File Size | 317049 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424473151 |
| ISSN | 10987584 |
| e-ISBN | 9781424473175 |
| e-ISBN | 9781424473168 |
| DOI | 10.1109/FUZZY.2011.6007323 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-06-27 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Symbiosis Neural networks Immune system Fuzzy systems Algorithm design and analysis Encoding Entropy control problems Compensatory fuzzy operator neural fuzzy network symbiotic evolution immune system algorithm |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Artificial Intelligence Theoretical Computer Science Software |
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