Dempster Shafer Structure-Fuzzy Number Based Uncertainty Modeling in Human Health Risk Assessment

Palash Dutta
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Palash Dutta: Department of Mathematics, Dibrugarh University, Dibrugarh, India

International Journal of Fuzzy System Applications (IJFSA), 2016, vol. 5, issue 2, 96-117

Abstract: In risk assessment, generally model parameters are affected by uncertainty arises due to vagueness, imprecision, lack of data, small sample sizes etc. Fuzzy set theory and Dempster-Shafer theory (In short DST) of evidence should be explored to handle this type of uncertainty. Representation of parameters of risk assessment models may be Dempster-Shafer structure (in short DSS) and fuzzy numbers. To deal with such situations, it is important to device new techniques. This paper presents two algorithms to combine Dempster-Shafer structure with generalized/normal fuzzy focal elements, generalized/normal fuzzy numbers within the same framework. Sampling technique for evidence theory and alpha-cut for fuzzy numbers are considered to execute the algorithms. Finally, results are obtained in the form of fuzzy numbers (normal/generalized) at different fractiles.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jfsa00:v:5:y:2016:i:2:p:96-117

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