Interpretability-preserving genetic optimization of linguistic terms in fuzzy models for fuzzy ordered classification: An ecological case study

DOI10.1016/j.ijar.2006.03.003zbMath1107.68450OpenAlexW2076760025WikidataQ60258009 ScholiaQ60258009MaRDI QIDQ868124

Ester Van Broekhoven, Bernard De Baets, Veronique Adriaenssens

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.2006.03.003

zbMATH Keywords

genetic algorithmsinterpretabilitylinguistic fuzzy modelsfuzzy ordered classifiershabitat suitability models

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10) Ecology (92D40) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items

Learning partial ordinal class memberships with kernel-based proportional odds models ⋮ Learning weighted linguistic fuzzy rules by using specifically-tailored hybrid estimation of distribution algorithms ⋮ Piecewise parametric polynomial fuzzy sets ⋮ A new probabilistic fuzzy model: Fuzzification-Maximization (FM) approach ⋮ Two-sample Kolmogorov-Smirnov fuzzy test for fuzzy random variables ⋮ Logic-based fuzzy networks: a study in system modeling with triangular norms and uninorms

Uses Software

• Genocop

Cites Work

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• Interpretability issues in fuzzy modeling
• Accuracy improvements in linguistic fuzzy modeling
• FS-FOIL: An inductive learning method for extracting interpretable fuzzy descriptions
• Ten years of genetic fuzzy systems: Current framework and new trends.
• A new approach to clustering