Diagnostic Inference with the Dempster-Shafer Theory and a Fuzzy Input
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.
KeywordsDempster-Shafer theory Fuzzy sets Diagnosis support
This research was supported by statutory funds of the Institute of Electronics, Silesian University of Technology.
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