New Similarity and Entropy Measures of Temporal Complex Neutrosophic Set and its Application in Multi-Criteria Decision Making

The Temporal complex neutrosophic set (TCNS) is an effective structure for resolving information that has uncertain, indeterminate, and timerelated factors in decision-making problems. In the last decade, many researchers focused on estimating the vagueness and ambiguity in knowledge using the theory of neutrosophic sets or extensions of neutrosophic sets. Similarity and entropy measures are valuable tools to measure information with the aim of dealing with real-life multi-criteria decisionmaking (MCDM) problems. However, the existing method did not care or interest in the information measures of TCNS. This paper proposes several new similarity and entropy measures under the TCNS environment. The suggested measurements have been confirmed and proven to concede with the manifest definition of the similarity and entropy measure for the TCNS. Finally, a numerical example related to deciding on a tourist terminus in Vietnam is given to confirm the practical applicability of the proposed measures. The numerical example proves that the proposed similarity and entropy measures of TCNS can produce accurate and reasonable results for decision-making problems in the real world.