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Learning of interval and general type-2 fuzzy logic systems using simulated annealing: theory and practice [PDF]
Information Sciences, 2016 This paper reports the use of simulated annealing to design more efficient fuzzy logic systems to model problems with associated uncertainties. Simulated annealing is used within this work as a method for learning the best configurations of interval and ...
Ahmadi, S. +3 more
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Hybrid Learning for General Type-2 TSK Fuzzy Logic Systems [PDF]
Algorithms, 2017 This work is focused on creating fuzzy granular classification models based on general type-2 fuzzy logic systems when consequents are represented by interval type-2 TSK linear functions. Due to the complexity of general type-2 TSK fuzzy logic systems, a
Mauricio A. Sanchez +3 more
doaj +3 more sources
Complex & Intelligent Systems, 2022 The paper performs the center-of-sets (COS) type-reduction (TR) and de-fuzzification for Takagi–Sugeno–Kang (TSK) type general type-2 fuzzy logic systems (GT2 FLSs) on the basis of the $$\alpha$$ α -planes expression of general type-2 fuzzy sets ...
Yang Chen
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IEEE Access, 2022 Studying the block of center-of-sets (COS) type-reduction (TR) for Takagi Sugeno Kang (TSK) inference-based general type-2 fuzzy logic systems (GT2 FLSs) is meaningful for applying the systems.
Yang Chen
doaj +3 more sources
Complex & Intelligent SystemsGeneral type-2 fuzzy logic systems (GT2 FLSs) based on the $$\alpha$$ α -planes representation of general T2 fuzzy sets (FSs) have become more accessible to FL investigators in recent years.
Yang Chen
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Automatic learning of general type-2 fuzzy logic systems using simulated annealing [PDF]
2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2014 This paper reports on a new approach for automatic learning of general type-2 fuzzy logic systems (GT2FLSs) using simulated annealing (SA). The learning process in this work starts without an initial interval type-2 fuzzy system and has an objective to optimize all membership function parameters involved in the general type-2 fuzzy set in two stages ...
Almaraashi, Majid +2 more
openaire +4 more sources
Complex & Intelligent Systems, 2022 AbstractGeneral type-2 (GT2) fuzzy logic systems (FLSs) become a popular research topic for the past few years. Usually the Karnik–Mendel algorithms are the most prevalent approach to complete the type-reduction. Nonetheless, the iterative quality of these types of computational intensive algorithms might impede applying them. For the improved types of
Yang Chen
openaire +2 more sources
Edge Detection Method Based on General Type-2 Fuzzy Logic Applied to Color Images
Information, 2017 This paper presents a new general type-2 fuzzy logic method for edge detection applied to color format images. The proposed algorithm combines the methodology based on the image gradients and general type-2 fuzzy logic theory to provide a powerful edge ...
Claudia I. Gonzalez +2 more
doaj +2 more sources
Design of Noniterative Algorithms for Takagi Sugeno Kang Type General Type-2 Fuzzy Logic Systems [PDF]
, 2022 Abstract The paper performs the center-of-sets (COS) type-reduction (TR) and defuzzification for Takagi Sugeno Kang (TSK) type general type-2 fuzzy logic systems (GT2 FLSs) on the basis of the T-planes expression of general type-2 fuzzy sets. Actually, comparing the popular Karnik-Mendel (KM) algorithms with other noniterative algorithms is an ...
Yang Chen, Chenxi Li, Jiaxiu Yang
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Forecasting by TSK general type‐2 fuzzy logic systems optimized with genetic algorithms
Optimal Control Applications and Methods, 2017 SummaryResearching the theory and applications of general type‐2 fuzzy logic systems (GT2 FLSs) has become a hot orientation in recent years. The permanent‐magnetic drive (PMD) affected by uncertainties is an emerging technology. This paper designs a type of Takagi‐Sugeno‐Kang GT2 FLSs to investigate PMD temperature forecasting problems.
Yang Chen, Dazhi Wang, Wu Ning
openaire +3 more sources