Hongwei Wu
Mendel, J.M.
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
This paper appears in: Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on Publication Date: 25-29 July 2004
Volume: 2
On page(s):
1099
- 1104 vol.2
ISSN: 1098-7584
ISBN: 0-7803-8353-2
Digital Object Identifier: 10.1109/FUZZY.2004.1375564
Current Version Published: 2005-01-10
Abstract
We investigate ten compensatory operators and SOWA operators in the framework of Mamdani interval type-2 fuzzy logic systems (FLS) so that for the first time the uncertainties originating from descriptive words, connector words and data can be simultaneously modeled. Our investigations show that: 1) for a Mamdani singleton interval type-2 FLS all the ten operators can be implemented and optimized; and 2) for a Mamdani non-singleton interval type-2 FLS the multiplicative compensatory operator that uses the product t-norm and maximum t-conorm, ΦpMCA, can be implemented and optimized. We apply ΦpMCA to chaotic time-series prediction where the observations are corrupted by non-stationary noise. Our experimental results show that by incorporating ΦpMCA into a Mamdani interval type-2 FLS it may take less time to train an interval type-2 FLS to achieve a satisfactory performance, and the resulting system is more robust to noise.
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