A genetic learning process for the scaling factors, granularity and contexts of the fuzzy rule-based system data base
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Publication:1602481
DOI10.1016/S0020-0255(01)00143-8zbMath0996.68157WikidataQ62608501 ScholiaQ62608501MaRDI QIDQ1602481
Luis Magdalena, Oscar Cordón, Pedro Villar, Francisco Herrera
Publication date: 23 June 2002
Published in: Information Sciences (Search for Journal in Brave)
Related Items (11)
Optimization of rational-powered membership functions using extended Kalman filter ⋮ Extracting complex linguistic data summaries from personnel database via simple linguistic aggregations ⋮ SUM NORMAL OPTIMIZATION OF FUZZY MEMBERSHIP FUNCTIONS ⋮ Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning ⋮ Genetic learning of accurate and compact fuzzy rule based systems based on the 2-tuples linguistic representation ⋮ Linguistic modeling with hierarchical systems of weighted linguistic rules ⋮ Ten years of genetic fuzzy systems: Current framework and new trends. ⋮ FEATURE SELECTION AND GRANULARITY LEARNING IN GENETIC FUZZY RULE-BASED CLASSIFICATION SYSTEMS FOR HIGHLY IMBALANCED DATA-SETS ⋮ A clustering and SVM regression learning-based spatiotemporal fuzzy logic controller with interpretable structure for spatially distributed systems ⋮ Learning the membership function contexts for mining fuzzy association rules by using genetic algorithms ⋮ A genetic learning process for the scaling factors, granularity and contexts of the fuzzy rule-based system data base
Uses Software
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