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Structure Identification of TSK-Fuzzy Systems Using Genetic Programming (2000)
| Content Provider | CiteSeerX |
|---|---|
| Author | Hoffmann, Frank Nelles, Oliver |
| Abstract | This paper explores a new approach to structure identi cation of TakagiSugeno -Kang (TSK) Fuzzy Models. We employ Genetic Programming (GP) to nd an optimal partition of the input space into Gaussian, axis-orthogonal fuzzy sets. We compare the GP approach with a greedy partition algorithm (LOLIMOT) for modeling an engine characteristic map. |
| File Format | |
| Publisher Date | 2000-01-01 |
| Access Restriction | Open |
| Subject Keyword | Fuzzy Model Optimal Partition Structure Identification Gp Approach Input Space Engine Characteristic Map Takagisugeno Kang Greedy Partition Algorithm Genetic Programming Axis-orthogonal Fuzzy Set Tsk-fuzzy System Using Genetic Programming Structure Identi Cation |
| Content Type | Text |
| Resource Type | Article |