Genetic learning of accurate and compact fuzzy rule based systems based on the 2-tuples linguistic representation

DOI10.1016/J.IJAR.2006.02.007zbMath1109.68087OpenAlexW2028933072WikidataQ104701797 ScholiaQ104701797MaRDI QIDQ868122

N. E. Zubov

Publication date: 19 February 2007

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2006.02.007

zbMATH Keywords

learninggenetic algorithmsfuzzy rule-based systemsinterpretability-accuracy trade-offlinguistic 2-tuples representation

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Reasoning under uncertainty in the context of artificial intelligence (68T37) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (10)

Extracting complex linguistic data summaries from personnel database via simple linguistic aggregations ⋮ The interpretability and scalability of linguistic-rule-based systems for solving regression problems ⋮ A MULTI-OBJECTIVE GENETIC ALGORITHM FOR TUNING AND RULE SELECTION TO OBTAIN ACCURATE AND COMPACT LINGUISTIC FUZZY RULE-BASED SYSTEMS ⋮ Identification of fuzzy inference systems by means of a multiobjective opposition-based space search algorithm ⋮ On the Use of Participatory Genetic Fuzzy System Approach to Develop Fuzzy Models ⋮ Learning weighted linguistic fuzzy rules by using specifically-tailored hybrid estimation of distribution algorithms ⋮ Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets ⋮ Piecewise parametric polynomial fuzzy sets ⋮ A new probabilistic fuzzy model: Fuzzification-Maximization (FM) approach ⋮ FUZZY BILEVEL PROGRAMMING: MULTI-OBJECTIVE AND MULTI-FOLLOWER WITH SHARED VARIABLES

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