Special Issue "Type-2 Fuzzy Logic: Theory, Algorithms and Applications"
Deadline for manuscript submissions: closed (20 December 2019) | Viewed by 10783
Interests: fuzzy logic; type-2 fuzzy logic; fuzzy control; hybrid intelligent systems
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In 1965, Prof. L. Zadeh introduced the concept of fuzzy sets (FSs) to represent uncertain system parameters. However, in many real-world systems, uncertainty appears for multiple reasons. In such a scenario, uncertainty modelling capabilities of type 1 (T1) or traditional FSs are quite limited, so Zadeh himself came up with the concept of type-2 FSs in 1975. However, for more than a decade, these types of FSs got very little attention from the scientific community. Interestingly, from 1990, researchers started investigating the T2 FSs, or more specifically the interval type-2 (IT2) FSs, and successfully applied the same concept for realistic uncertainty modelling in a number of applications.
Very recently, a new research trend has been noticed, in which researchers have shifted their focus from the IT2 FSs to the general type 2 (GT2) FSs and explored better results in many applications. This has further been motivated by some of Prof. J. M. Mendel´s recent works, in which he has nicely shown that if proper care is taken during the designing phase, an IT2 fuzzy logic system (FLS) shall always produce better (or at least equal) performance than a T1 FLS. Similarly, a GT2 FLS has the capability to give better than (or at least equal performance to) a IT2 FLS. Nevertheless, the growth of research carried out on the T2 FSs and T2 FLSs is far less than the volume of research conducted on T1 FSs. Therefore, this Special Issue aims to introduce cutting-edge research concepts on T2 FSs and systems and their applications in a number of emerging systems including (but not limited to) the following:
- T2 FS-based uncertainty modelling in Cyber-physical systems
- Social network analysis under T2 fuzzy uncertainty
- T2 FLSs in cyber security
- T2 FS-based uncertainty modelling in big data analytics
- Multi-media applications with fuzzy uncertainty
- T2 FSs for image processing
- T2 FSs in evolutionary optimization
- T2 FSs and T2 FLSs in machine learning
- T2 FSs and T2 FLSs deep learning
- T2 FLSs for power systems
- T2 FSs for energy optimization
- T2 FSs and T2 FLSs green computing
- T2 FS-based uncertainty modelling vehicle routing problem
- And other application areas with T2 FS-based uncertainty modelling
Prof. Dr. Oscar Castillo
Manuscript Submission Information
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- type-2 fuzzy logic
- type-2 fuzzy control
- type-2 fuzzy pattern recognition
- type-2 fuzzy neural networks
- type-2 fuzzy in metaheuristics