Guest Editorial: Deep Fuzzy Models

Alexander Gegov; Uzay Kaymak; Joao Sousa

doi:10.1109/TFUZZ.2020.2996512

Guest Editorial: Deep Fuzzy Models

Alexander Gegov, Uzay Kaymak, Joao Sousa

School of Computing

Research output: Contribution to journal › Editorial › peer-review

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Abstract

This special issue features recent developments and emerging topics in the area of deep fuzzy models that address some of the problems and limitations above. These models have been known under different names such as hierarchical fuzzy systems and fuzzy networks. They are usually well suited for performing multiple functional composition at either crisp or linguistic level. Moreover, they have the potential of handling effectively and efficiently data that is not well defined by means of a fuzzy approach. Also, deep fuzzy models can be used in both passive and active manner with regard to the environment due to their generic structure. Finally, these models have a fairly high level of transparency due to their rule base nature.

Original language	English
Pages (from-to)	1191-1194
Number of pages	4
Journal	IEEE Transactions on Fuzzy Systems
Volume	28
Issue number	7
DOIs	https://doi.org/10.1109/TFUZZ.2020.2996512
Publication status	Published - 1 Jul 2020

Keywords

deep fuzzy models
hierarchical fuzzy systems
fuzzy networks
neuro fuzzy systems
fuzzy neural networks
deep fuzzy systems
fuzzy trees
chained fuzzy systems

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10.1109/TFUZZ.2020.2996512

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abstract = "This special issue features recent developments and emerging topics in the area of deep fuzzy models that address some of the problems and limitations above. These models have been known under different names such as hierarchical fuzzy systems and fuzzy networks. They are usually well suited for performing multiple functional composition at either crisp or linguistic level. Moreover, they have the potential of handling effectively and efficiently data that is not well defined by means of a fuzzy approach. Also, deep fuzzy models can be used in both passive and active manner with regard to the environment due to their generic structure. Finally, these models have a fairly high level of transparency due to their rule base nature. ",

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Guest Editorial: Deep Fuzzy Models

Abstract

Keywords

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