The sequence of neutrosophic soft sets and a decision-making problem in medical diagnosis

Abstract

The object recognition problems realized in uncertain environments have played a paramount role in decision-making. In recent years, neutrosophic soft sets (NS-sets), a combination of soft and neutrosophic sets, have emerged as outstanding candidates in this field. If neutrosophic sets are used to handle problems involving imprecise, indeterminate, and inconsistent data, soft sets are used to deal with uncertainties that classical tools cannot control. This paper defines a new concept based on NS-sets, called the sequence of NS-sets (NSS-sequence). Their inclusions, special types, operations, distances are determined with reasonable, convincing, and well-proven properties. Furthermore, we also propose an algorithm for the decision-making problem on NS-sequence and apply it in medical diagnosis by a real-life experiment. Finally, intending to verify its validity and feasibility, we compare our algorithm to the algorithm for the decision-making problem on time NS-set (tNS-set) through the real-life mentioned earlier by Alkhazaleh. Our work also shows that the proposed algorithm on NS-sequence has the same results as that offered by Alkhazaleh, and the tNS-set is just a particular case of the NSS-sequence.