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Fuzzy-DSS Human Health Risk Assessment Under Uncertain Environment
Abstract
It is always utmost essential to accumulate knowledge on the nature of each and every accessible data, information, and model parameters in risk assessment. It is noticed that more often model parameters, data, information are fouled with uncertainty due to lack of precision, deficiency in data, diminutive sample sizes. In such environments, fuzzy set theory or Dempster-Shafer theory (DST) can be explored to represent this type of uncertainty. Most frequently, both types of uncertainty representation theories coexist in human health risk assessment and need to merge within the same framework. For this purpose, this chapter presents two algorithms to combine Dempster-Shafer structure (DSS) with generalized/normal fuzzy focal elements, generalized/normal fuzzy numbers within the same framework. Computer codes are generated using Matlab M-files. Finally, human health risk assessment is carried out under this setting and it is observed that the results are obtained in the form of fuzzy numbers (normal/generalized) at different fractiles.
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