Monotone Data Samples Do Not Always Produce Monotone Fuzzy If- Then Rules: Learning with Ad hoc and System Identification Methods
In this paper, ad hoc and system identification methods are used to generate fuzzy If-Then rules for a zeroorder Takagi-Sugeno-Kang (TSK) Fuzzy Inference System (FIS) using a set of multi-attribute monotone data. Convex and normal trapezoidal fuzzy sets, with a strong fuzzy partition strategy,...
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| Main Authors: | , , |
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| Format: | E-Article |
| Language: | English |
| Published: |
IEEE
2017
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/17423/1/Monotone%20Data%20Samples%20Do%20Not%20Always%20Produce%20Monotone%20Fuzzy%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/17423/ http://ieeexplore.ieee.org/document/8015386/ |
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