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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 WuKarnik-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 ProceedingsPagination
1 - 6Publisher
IEEELocation
Istanbul, TurkeyPlace of publication
Piscataway, N.J.Start date
2015-08-02End date
2015-08-05ISSN
1544-5615ISBN-13
9781467374286Language
engPublication classification
E Conference publication; E1 Full written paper - refereedCopyright notice
2015, IEEEEditor/Contributor(s)
A Yazici, N Pal, U Kaymak, T Martin, H Ishibuchi, C Lin, J Sousa, B TutmezTitle of proceedings
FUZZ-IEEE 2015: Proceedings of the IEEE International Conference on Fuzzy SystemsUsage metrics
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