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Input selection in data-driven fuzzy modeling

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3 Author(s)
Gaweda, A.E. ; Dept. of Electr. & Comput. Eng., Louisville Univ., KY, USA ; Zurada, J.M. ; Setiono, R.

An iterative backward selection method for determination of relevant input variables in data-driven fuzzy modeling is presented. The method utilizes parameters of the Takagi-Sugeno model as a factor to determine the significance of input variables. As a result, it is less computationally intensive than most of the existing methods for input variable selection

Published in:

Fuzzy Systems, 2001. The 10th IEEE International Conference on  (Volume:3 )

Date of Conference:

2001