A prototype-based rule inference system incorporating linear functions

Tang Yongchuan, J Lawry

Research output: Contribution to journalArticle (Academic Journal)peer-review

12 Citations (Scopus)

Abstract

A calculus of appropriateness measures of linguistic expressions is proposed, which is based on the prototype theory and random set theory interpretation of vague concepts. A prototype-based rule inference system is then introduced to incorporate linguistic labels in the rule antecedents and linear functions in the consequents of rules. And a rule learning algorithm is developed by combining a new clustering algorithm and a conjugate gradient algorithm. The proposed prototype-based inference system is then applied to a number of benchmark prediction problems including a nonlinear two-dimensional surface, the Mackey–Glass time series and the sunspot time-series. Results suggest that the proposed model is very robust and can perform well in high-dimensional noisy data.
Translated title of the contributionA prototype-based rule inference system incorporating linear functions
Original languageEnglish
Pages (from-to)2831 - 2853
Number of pages22
JournalFuzzy Sets and Systems
Volume161
Publication statusPublished - Nov 2010

Bibliographical note

Author of Publication Reviewed: Yongchuan Tang AND Jonathan Lawry

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