Linguistic modelling and information coarsening based on prototype theory and label semantics

DOI10.1016/j.ijar.2009.01.004zbMath1191.68699OpenAlexW2023949414MaRDI QIDQ962929

Yongchuan Tang, Jonathan Lawry

Publication date: 7 April 2010

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

Full work available at URL: https://doi.org/10.1016/j.ijar.2009.01.004

zbMATH Keywords

linguistic modellingknowledge extractionlabel semanticsprototype theoryGaussian-type density functioninformation coarseninglinguistic IF-THEN rulesmackey-glass time series predictionprototype-based clusteringsunspots time series prediction

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Related Items

A prototype-based rule inference system incorporating linear functions, A bipolar model of vague concepts based on random set and prototype theory, A label semantics approach to linguistic hedges, Multi-source information fusion model in rule-based Gaussian-shaped fuzzy control inference system incorporating Gaussian density function, Linguistic modelling and information coarsening based on prototype theory and label semantics, Information cells and information cell mixture models for concept modelling, Reasoning with doubly uncertain soft constraints, A review of applications of fuzzy sets to safety and reliability engineering

Uses Software

• LFOIL
• TDSL
• ANFIS
• TSDL

Cites Work

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