Monotone Data Samples Do Not Always Produce Monotone Fuzzy If- Then Rules: Learning with Ad hoc and System Identification Methods

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,...

Full description

Bibliographic Details
Main Authors: Chin, Ying Teh, Tay, Kai Meng, Chee, Peng Lim
Format: Article
Language:English
Published: IEEE 2017
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://ir.unimas.my/id/eprint/17423/
http://ir.unimas.my/id/eprint/17423/1/Monotone%20Data%20Samples%20Do%20Not%20Always%20Produce%20Monotone%20Fuzzy%20%28abstract%29.pdf

Internet

http://ir.unimas.my/id/eprint/17423/
http://ir.unimas.my/id/eprint/17423/1/Monotone%20Data%20Samples%20Do%20Not%20Always%20Produce%20Monotone%20Fuzzy%20%28abstract%29.pdf

Similar Items