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SYMMETRIC IMPLICATIONAL RESTRICTION METHOD of FUZZY INFERENCE

  • Yiming Tang
  • , Wenbin Wu
  • , Youcheng Zhang
  • , Witold Pedrycz
  • , Fuji Ren
  • , Jun Liu

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The symmetric implicational method is revealed from a different perspective based upon the restriction theory, which results in a novel fuzzy inference scheme called the symmetric implicational restriction method. Initially, the SIR-principles are put forward, which constitute optimized versions of the triple I restriction inference mechanism. Next, the existential requirements of basic solutions are given. The supremum (or infimum) of its basic solutions is achieved from some properties of fuzzy implications. The conditions are obtained for the supremum to become the maximum (or the infimum to be the minimum). Lastly, four concrete examples are provided, and it is shown that the new method is better than the triple I restriction method, because the former is able to let the inference more compact, and lead to more and superior particular inference schemes.

Original languageEnglish
Pages (from-to)688-713
Number of pages26
JournalKybernetika
Volume57
Issue number4
DOIs
Publication statusPublished - 2021

Keywords

  • Compositional rule of inference
  • Continuity
  • Fuzzy entropy
  • Fuzzy inference

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Information Systems
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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