Design of Takagi Sugeno Kang Type Interval Type-2 Fuzzy Logic Systems Optimized with Hybrid Algorithms-Reference-Cited by-同舟云学术

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Design of Takagi Sugeno Kang Type Interval Type-2 Fuzzy Logic Systems Optimized with Hybrid Algorithms

Published:2022-10-21 Issue:2 Volume:25 Page:868-879
ISSN:1562-2479
Container-title:International Journal of Fuzzy Systems
language:en
Short-container-title:Int. J. Fuzzy Syst.

Author:

Chen Yang,Yang Jiaxiu,Li Chenxi

Funder

National Natural Science Foundation of China

Doctoral Start-up Foundation of Liaoning Province

Foundation of Liaoning Province Education Administration

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s40815-022-01410-z.pdf

Reference50 articles.

1. Zarandi, M.H.F., Rezaee, B., Turksen, I.B.: A type-2 fuzzy rule-based expert system model for stock price analysis. Expert Syst. Appl. 36(1), 139–154 (2009)

2. Bernardo, D., Hagras, H., Tsang, E.: A genetic type-2 fuzzy logic based system for the generation of summarized linguistic predictive models for financial applications. Soft. Comput. 17(12), 2185–2201 (2013)

3. Chen, Y., Wang, D.Z., Tong, S.C.: Forecasting studies by designing Mamdani interval type-2 fuzzy logic systems: with the combination of BP algorithms and KM algorithms. Neurocomputing 174, 1133–1146 (2016)

4. Khosravi, A., Nahavandi, S.: Load forecasting using interval type-2 fuzzy logic systems: optimal type reduction. IEEE Trans. Industr. Inf. 10(2), 1055–1063 (2014)

5. Khosravi, A., Nahavandi, S., Creighton, D., Srinivasan, D.: Interval type-2 fuzzy logic systems for load forecasting: a comparative study. IEEE Trans. Power Syst. 27(3), 1274–1282 (2012)

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