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- W202063358 abstract "Abstract System modeling with fuzzy rule-based systems (FRBSs), i.e. fuzzy modeling (FM), usually comes with two contradictory requirements in the obtained model: the interpretability, capability to express the behavior of the real system in an understandable way, and the accuracy, capability to faithfully represent the real system. While linguistic FM (mainly developed by linguistic FRBSs) is focused on the interpretability, precise FM (mainly developed by Takagi-Sugeno-Kang FRBSs) is focused on the accuracy. Since both criteria are of vital importance in system modeling, the balance between them has started to pay attention in the fuzzy community in the last few years.The chapter analyzes mechanisms to find this balance by improving the interpretability in linguistic FM: selecting input variables, reducing the fuzzy rule set, using more descriptive expressions, or performing linguistic approximation; and in precise FM: reducing the fuzzy rule set, reducing the number of fuzzy sets, or exploiting the local description of the rules.KeywordsIEEE TransactionFuzzy SystemFuzzy RuleFuzzy ModelingLinguistic TermThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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- W202063358 date "2003-01-01" @default.
- W202063358 modified "2023-10-11" @default.
- W202063358 title "Interpretability Improvements to Find the Balance Interpretability-Accuracy in Fuzzy Modeling: An Overview" @default.
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- W202063358 doi "https://doi.org/10.1007/978-3-540-37057-4_1" @default.
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