Study on sampling-based discrete noniterative algorithms for centroid type-reduction of interval type-2 fuzzy logic systems-Reference-Cited by-同舟云学术

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Study on sampling-based discrete noniterative algorithms for centroid type-reduction of interval type-2 fuzzy logic systems

Published:2020-05-04 Issue:15 Volume:24 Page:11819-11828
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Chen Yang

Funder

National Natural Science Foundation of China

Natural Science Foundation of Liaoning Province

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s00500-020-04998-2.pdf

Reference48 articles.

1. Biglarbegian M, Melek WW, Mendel JM (2010) On the stability of interval type-2 TSK fuzzy logic systems. IEEE Trans Syst Man Cybern B Cybern 40(3):798–818

2. Biglarbegian M, Melek WW, Mendel JM (2011) On the robustness of type-1 and interval type-2 fuzzy logic systems in modeling. Inf Sci 181(7):1325–1347

3. Castillo O, Amador-Angulo L, Castro JR et al (2016) A comparative study of type-1 fuzzy logic systems, interval type-2 fuzzy logic systems and generalized type-2 fuzzy logic systems in control problems. Inf Sci 354(c):257–274

4. Castillo O, Melin P, Ontiveros E et al (2019) A high-speed interval type 2 fuzzy system approach for dynamic parameter adaptation in metaheuristics. Eng Appl Artif Intell 85:666–680

5. Cervantes L, Castillo O (2015) Type-2 fuzzy logic aggregation of multiple fuzzy controllers for airplane flight control. Inf Sci 324:247–256

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1. Interval type-2 fuzzy systems on the basis of vague partitions and their approximation properties;Computational and Applied Mathematics;2024-03-19

2. Study on centroid type-reduction of general type-2 fuzzy logic systems with sensible beginning weighted enhanced Karnik–Mendel algorithms;Soft Computing;2023-05-09

3. Design and application of Nagar-Bardini structure-based interval type-2 fuzzy logic systems optimized with the combination of backpropagation algorithms and recursive least square algorithms;Expert Systems with Applications;2023-01

4. Study on non-iterative algorithms for center-of-sets type-reduction of Takagi–Sugeno–Kang type general type-2 fuzzy logic systems;Complex & Intelligent Systems;2022-12-19

5. Design of Takagi Sugeno Kang Type Interval Type-2 Fuzzy Logic Systems Optimized with Hybrid Algorithms;International Journal of Fuzzy Systems;2022-10-21

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