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For: Magdalena L. Semantic interpretability in hierarchical fuzzy systems: Creating semantically decouplable hierarchies. Inf Sci (N Y) 2019;496:109-23. [DOI: 10.1016/j.ins.2019.05.016] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Number Cited by Other Article(s)
1
Łapa K. Increasing the explainability and trustiness of Wang–Mendel fuzzy system for classification problems. Appl Soft Comput 2024;167:112257. [DOI: 10.1016/j.asoc.2024.112257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2025]
2
An interpretable Neural Fuzzy Hammerstein-Wiener network for stock price prediction. Inf Sci (N Y) 2021. [DOI: 10.1016/j.ins.2021.06.076] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
3
Kluska J. Adaptive fuzzy control of state-feedback time-delay systems with uncertain parameters. Inf Sci (N Y) 2020. [DOI: 10.1016/j.ins.2020.06.015] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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