Health Risk Assessment through Incorporation of Dempster–Shafer Structure and Fuzzy Numbers within the Same Framework

Abstract

It is always most important to accrue knowledge on the features of each and every existing data, information and model parameters in risk assessment. It is observed that most frequently model parameters, data, information are fouled with uncertainty due to lack of precision, deficiency in data, diminutive sample sizes. In such situations, fuzzy set theory or Dempster–Shafer structure (DSS) can be explored to represent uncertainty. More often, both type of uncertainty representation theories coexist in health risk assessment and need to amalgamate. This paper presents two algorithms to combine DSS and fuzzy numbers (FNs) of different shapes. • The algorithms deal with the combination of DSS with fuzzy focal elements of different types and different fuzzy numbers of various types and shapes within the same framework. • Finally, non-cancer human health risk assessment is carried out under this setting. • Results are obtained in fuzzy numbers at different fractiles. The approaches presented here have the ability to be used in any mathematical model which represents real-world problems, in which model parameters are tainted with uncertainty, where representations of uncertain model parameters are DSS and fuzzy numbers with different shapes and types.