Chapter

Combining Experimentation and Theory

Volume 271 of the series Studies in Fuzziness and Soft Computing pp 301-327

Date:

Using Dempster-Shafer Structures to Provide Probabilistic Outputs in Fuzzy Systems Modeling

  • Ronald R. YagerAffiliated withMachine Intelligence Institute, Iona College Email author 
  • , Dimitar P. FilevAffiliated withFord Motor Company

* Final gross prices may vary according to local VAT.

Get Access

Abstract

Our interest is in providing a capability to include probabilistic outputs in fuzzy systems modeling. To accomplish this we use Dempster-Shafer belief structures. We first discuss some basic ideas from the Dempster-Shafer theory of evidence. We then describe Mamdani’s paradigm for fuzzy systems modeling which provided the pioneering framework for the many applications of fuzzy logic control. We then show how to use the Dempster-Shafer belief structure to provide machinery for including randomness in the fuzzy systems modeling process. We show how to this can be used to include various types of uncertainties including additive noise in the fuzzy systems modeling process. We next describe the Takagi-Sugeno approach to fuzzy systems modeling. Finally we use the Dempster-Shafer belief structure to enable the inclusion of probabilistic aspects in the output of the Takagi-Sugeno model.

Keywords

Mamdani Model fuzzy system modeling possibility-probability outputs