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Diagnostic Inference with the Dempster-Shafer Theory and a Fuzzy Input

  • Ewa StraszeckaEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 643)

Abstract

The present paper proposes a diagnosis support inference in which input evidence are fuzzy sets. Diagnostic rules are formulated as fuzzy focal elements in the Dempster-Shafer theory. An inclusion measure is used to evaluate matching knowledge with evidence and to calculate belief of the diagnosis. Data simulated for two diagnostic situations show that the method allow for using linguistic values as a diagnostic information.

Keywords

Dempster-Shafer theory Fuzzy sets Diagnosis support 

Notes

Acknowledgement

This research was supported by statutory funds of the Institute of Electronics, Silesian University of Technology.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Institute of Electronics, Faculty of Automatic Control, Electronics and Computer ScienceSilesian University of TechnologyGliwicePoland

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