Structure Identi cation of TSK-Fuzzy Systems using Genetic Programming
نویسندگان
چکیده
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.
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