Fine–kinney-based occupational risk assessment using single-valued neutrosophic topsis

Neutrosophic sets are initially recommended by Smarandache (First international conference on neutrosophy, neutrosophic logic, set, probability, and statistics. University of New Mexico, Gallup, NM, pp 338–353, 2002 [1]). These sets reflect uncertainty and vagueness in real-world problems better than classical fuzzy set theory. It takes into consideration three decision-making situations called indeterminacy, truthiness, and falsity. In Zadeh traditional fuzzy set theory, there is just membership function fuzzy set degree. But, in neutrosophic environment, it considers three membership functions. Unlike intuitionistic fuzzy sets, an indeterminacy degree is considered. In this chapter, we applied a special form of neutrosophic set as single-valued neutrosophic set (SVNs) with the technique for order preference by similarity to ideal solution (TOPSIS) under the concept of Fine–Kinney occupational risk assessment. Since the mere TOPSIS has failed to handle imprecise and vague information which usually exist in real-world problems, we follow the integration of SVNs and TOPSIS. To demonstrate the applicability of the novel approach, a case study of risk assessment of a wind turbine in times of operation was provided. Comparative analysis with some similar approaches and sensitivity analysis by changing the weights of Fine–Kinney parameters are carried out. Finally, the Python implementation of the proposed approach is executed to be useful for those concerned in the future.