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Switch point finding using polynomial regression for fuzzy type reduction algorithms

conference contribution
posted on 2015-01-01, 00:00 authored by Syed Moshfeq Salaken, Abbas KhosraviAbbas Khosravi, Saeid Nahavandi, D Wu
Karnik-Mendel (KM) algorithm is the most widely used type reduction (TR) method in literature for the design of interval type-2 fuzzy logic systems (IT2FLS). Its iterative nature for finding left and right switch points is its Achilles heel. Despite a decade of research, none of the alternative TR methods offer uncertainty measures equivalent to KM algorithm. This paper takes a data-driven approach to tackle the computational burden of this algorithm while keeping its key features. We propose a regression method to approximate left and right switch points found by KM algorithm. Approximator only uses the firing intervals, rnles centroids, and FLS strnctural features as inputs. Once training is done, it can precisely approximate the left and right switch points through basic vector multiplications. Comprehensive simulation results demonstrate that the approximation accuracy for a wide variety of FLSs is 100%. Flexibility, ease of implementation, and speed are other features of the proposed method.

History

Event

IEEE International Conference on Fuzzy Systems (2015 : Istanbul, Turkey)

Series

IEEE International Fuzzy Systems Conference Proceedings

Pagination

1 - 6

Publisher

IEEE

Location

Istanbul, Turkey

Place of publication

Piscataway, N.J.

Start date

2015-08-02

End date

2015-08-05

ISSN

1544-5615

ISBN-13

9781467374286

Language

eng

Publication classification

E Conference publication; E1 Full written paper - refereed

Copyright notice

2015, IEEE

Editor/Contributor(s)

A Yazici, N Pal, U Kaymak, T Martin, H Ishibuchi, C Lin, J Sousa, B Tutmez

Title of proceedings

FUZZ-IEEE 2015: Proceedings of the IEEE International Conference on Fuzzy Systems

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