Comparison of clustering algorithms in the identification of Takagi--Sugeno models: a hydrological case study

DOI10.1016/J.FSS.2006.04.007zbMath1103.68734OpenAlexW2036272275WikidataQ58874083 ScholiaQ58874083MaRDI QIDQ853412

Bernard De Baets, Niko E. C. Verhoest, Hilde Vernieuwe

Publication date: 15 November 2006

Published in: Fuzzy Sets and Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.fss.2006.04.007

zbMATH Keywords

groundwater flowfuzzy clusteringphysicsTakagi--Sugeno models

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Hydrology, hydrography, oceanography (86A05) Computing methodologies and applications (68U99)

Related Items (1)

A clustering algorithm based TS fuzzy model for tracking dynamical system data

Cites Work

• Subtractive clustering based modeling of job sequencing with parametric search
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• CAPILLARY CONDUCTION OF LIQUIDS THROUGH POROUS MEDIUMS
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