Entropy Measures Of Distance And Similarity Of Q Neutrosophic Soft Sets And Some Applications
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Entropy, Measures of Distance and Similarity of Q-Neutrosophic Soft Sets and Some Applications
In this study, the tools that measure the similarity, distance and the degree of fuzziness of Q-neutrosophic soft sets are presented. The definitions of distance, similarity and measures of entropy are introduced. Some formulas for Q-neutrosophic soft entropy were presented. The known Hamming, Euclidean and their normalized distances are generalized to make them well matched with the idea of Q-neutrosophic soft set. The distance measure is subsequently used to define the measure of similarity. Lastly, we expound three applications of the measures of Q-neutrosophic soft sets by applying entropy and the similarity measure to a medical diagnosis and decision making problems.
A New Development of Entropy and Similarity Measures in Temporal Complex Neutrosophic Environments for Tourist Destination Selection
In human existence, making decisions is a common event. Various techniques have been devised to tackle decision-making troubles in practical situations. Over the past ten years, a great deal of study has concentrated on quantifying the degree of ambiguity and unpredictability in knowledge using the concept of neutrosophic sets or extensions thereof. An efficient framework for handling information in decision-making problems involving uncertain, indeterminate, and time-related aspects is the Temporal Complex Neurosophic Set (TCNS). Measures of entropy and similarity can be helpful for evaluating data to solve multicriteria decisionmaking (MCDM) challenges in practical situations. However, TCNS information measurements were of no concern or relevance to the current technique. In the context of the TCNS, this work suggests multiple novel similarity and entropy measurements. The proposed metrics have been validated and shown to comply with the explicit definition of the entropy measure and similarity for the TCNS. The novel similarity and entropy measures on the TCNS environment are proposed in this research. The four similarity measures on the TCNS contain Dice, Jaccard, Cosine, and Cotangent. Also, a numerical example concerning selecting a Vietnam tourist destination is provided to validate the usefulness of the suggested measures. The practical application shows that proposed TCNS similarity and entropy metrics can produce accurate and significant outcomes for real-world decision-making problems.
An Approach toward a Q-Neutrosophic Soft Set and Its Application in Decision Making
A neutrosophic set was proposed as an approach to study neutral uncertain information. It is characterized through three memberships, T, I and F, such that these independent functions stand for the truth, indeterminate, and false-membership degrees of an object. The neutrosophic set presents a symmetric form since truth enrolment T is symmetric to its opposite false enrolment F with respect to indeterminacy enrolment I that acts as an axis of symmetry. The neutrosophic set was further extended to a Q-neutrosophic soft set, which is a hybrid model that keeps the features of the neutrosophic soft set in dealing with uncertainty, and the features of a Q-fuzzy soft set that handles two-dimensional information. In this study, we discuss some operations of Q-neutrosophic soft sets, such as subset, equality, complement, intersection, union, AND operation, and OR operation.