Generalisation of scale and move transformation-based fuzzy interpolation

Qiang Shen, Longzhi Yang

Research output: Contribution to journalArticlepeer-review

45 Citations (Scopus)

Abstract

Fuzzy interpolative reasoning has been extensively studied due to its ability to enhance the robustness of fuzzy systems and reduce system complexity. In particular, the scale and move transformation-based approach is able to handle interpolation with multiple antecedent rules involving triangular, complex polygon, Gaussian and bell-shaped fuzzy membership functions. Also, this approach has been extended to deal with interpolation and extrapolation with multiple multi-antecedent rules. However, the generalised extrapolation approach based on multiple rules may not degenerate back to the basic crisp extrapolation based on two rules. Besides, the approximate function of the extended approach may not be continuous. This paper therefore proposes a new approach to generalising the basic fuzzy interpolation technique of in an effort to eliminate these limitations. Examples are given throughout the paper for illustration and comparative purposes. The result shows that the proposed approach avoids the identified problems, providing more reasonable interpolation and extrapolation.
Original languageEnglish
Pages (from-to)288-298
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Volume15
Issue number3
Publication statusPublished - May 2011

Keywords

  • sparse rule base
  • fuzzy interpolation and extrapolation
  • approximate function

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