Singular value-based fuzzy rule interpolation

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

In sparse fuzzy rule bases, conventional fuzzy reasoning methods can not reach a proper conclusion. To eliminate this problem interpolative reasoning has emerged in fuzzy research as a new topic. If the number of variables or the number of fuzzy terms is growing the size of rule bases increases exponentially, hence, the inference/control time also increases considerably. Interpolative reasoning can help to reduce the number of rules, but does not eliminate the problem of exponentially growing. Singular value based rule base reduction (FuzzySVD) methods have been published to various conventional methods. This paper introduces the extension of the FuzzySVD method to the specialized fuzzy rule interpolation method to achieve more significant reduction.

Original languageEnglish
Pages51-56
Number of pages6
Publication statusPublished - Dec 1 1997
EventProceedings of the 1997 International Conference on Intelligent Engineering Systems, INES - Budapest, Hungary
Duration: Sep 15 1997Sep 17 1997

Other

OtherProceedings of the 1997 International Conference on Intelligent Engineering Systems, INES
CityBudapest, Hungary
Period9/15/979/17/97

ASJC Scopus subject areas

  • Engineering(all)
  • Materials Science(all)

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  • Cite this

    Baranyi, P., Yam, Y., & Koczy, L. T. (1997). Singular value-based fuzzy rule interpolation. 51-56. Paper presented at Proceedings of the 1997 International Conference on Intelligent Engineering Systems, INES, Budapest, Hungary, .