Paper Info
Title
Realizing Deep High-Order TSK Fuzzy Classifier by Ensembling Interpretable Zero-Order TSK Fuzzy Subclassifiers
Abstract
Although high-order Takagi–Sugeno–Kang (TSK) fuzzy systems have demonstrated their computational advantages and simultaneously circumvent the weakness that the number of rules with the number of input variables and membership functions grows exponentially in both zero-order and first-order TSK fuzzy systems for complex modeling tasks, they still face two serious issues: incapability for a changing...
Year
DOI
Venue
2021
10.1109/TFUZZ.2020.3022574
IEEE Transactions on Fuzzy Systems
Keywords
DocType
Volume
Task analysis,Deep learning,Fuzzy systems,Linguistics,Training,Fuzzy sets,Classification algorithms
Journal
29
Issue
ISSN
Citations 
11
1063-6706
3
PageRank 
References 
Authors
0.43
11
4
Name
Order
Citations
PageRank
Bin Qin181.53
Kaname Narukawa229317.27
Hisao Ishibuchi37385503.41
Shitong Wang41485109.13