Fuzzy rule interpolation for multidimensional input spaces with applications

A case study

Kok Wai Wong, D. Tikk, Tamás D. Gedeon, L. Kóczy

Research output: Contribution to journalArticle

119 Citations (Scopus)

Abstract

Fuzzy rule based systems have been very popular in many engineering applications. However, when generating fuzzy rules from the available information, this may result in a sparse fuzzy rule base. Fuzzy rule interpolation techniques have been established to solve the problems encountered in processing sparse fuzzy rule bases. In most engineering applications, the use of more than one input variable is common, however, the majority of the fuzzy rule interpolation techniques only present detailed analysis to one input variable case. This paper investigates characteristics of two selected fuzzy rule interpolation techniques for multidimensional input spaces and proposes an improved fuzzy rule interpolation technique to handle multidimensional input spaces. The three methods are compared by means of application examples in the field of petroleum engineering and mineral processing. The results show that the proposed fuzzy rule interpolation technique for multidimensional input spaces can be used in engineering applications.

Original languageEnglish
Pages (from-to)809-819
Number of pages11
JournalIEEE Transactions on Fuzzy Systems
Volume13
Issue number6
DOIs
Publication statusPublished - Dec 2005

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Fuzzy rules
Fuzzy Rules
Interpolation
Interpolate
Engineering Application
Fuzzy Rule Base
Fuzzy Rule-based Systems
Petroleum
Petroleum engineering
Ore treatment
Knowledge based systems
Engineering
Processing

Keywords

  • Fuzzy rule interpolation
  • Multidimensional input spaces
  • Sparse fuzzy rules

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Artificial Intelligence

Cite this

Fuzzy rule interpolation for multidimensional input spaces with applications : A case study. / Wong, Kok Wai; Tikk, D.; Gedeon, Tamás D.; Kóczy, L.

In: IEEE Transactions on Fuzzy Systems, Vol. 13, No. 6, 12.2005, p. 809-819.

Research output: Contribution to journalArticle

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