Deng entropy in neutrosophic sets

The aim of this study is to define new Neutrosophic Evidence Sets (NECs) to provide additional probabilistic metrics that aim to address the uncertainty, ambiguity, incompleteness and inconsistency present in real-world information through neutrosophic sets (NES). Dempster-Shafer evidence theory is a very practical concept for addressing uncertain information. The basis of this theory lies in the Basic Probability Assignment (BPA), which adds a support system structure attributed only to the focal elements (FE). The basic element of NES consists of the Neutrosophic Basic Probability Assignment (NBPA), which consists of three members. The accuracy degree of FE can be done with the first BPA, the performance degree with the second BPA, and the performance degree with the last BPA. In NECs, each support degree of FE is shown separately without any limitation. Therefore, NECs is broader in scope. The NBPA method assigns the correctness support, combination support and false support degrees as well as these support degrees to a constraining collaboration of single and multiple subsets. This work carries out some information metric improvements for NECs, such as Neutrosophic Deng Entropy (NDE), Neutrosophic Cosine Similarity Measure (NCSM) and Neutrosophic Jousselme Distance (NJD). In continuation, an improved method based on Dempster-Shafer evidence theory (D-S evidence theory) is provided to combine the replicated evidences to increase the duplication of reliable evidences on one hand and minimize the length of unreliable evidences on the other hand. Finally, a case study is provided to demonstrate the features and superiority of this standard part, which includes sensor data integration for target identification.