Multi Criteria Decision Making Method Based On Similarity Measures Under Single Valued Neutrosophic Refined And Interval Neutrosophic Refined Environments
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Multi-criteria decision making method based on similarity measures under single-valued neutrosophic refined and interval neutrosophic refined environments
In this paper, we propose three similarity measure methods for single-valued neutrosophic refined sets and interval neutrosophic refined sets based on Jaccard, Dice and Cosine similarity measures of single-valued neutrosophic sets and interval neutrosophic sets.
Neutrosophic Multi-Criteria Decision Making
This book is a printed edition of the Special Issue "Neutrosophic Multi-Criteria Decision Making" that was published in Axioms
Roughness And Similarity Measure Of Rough Neutrosophic Multisets Using Vectorial Model Of Information
The roughness and similarity measure for two different information in the same universal set is useful in explaining the strength and completeness of the information given. Then, for rough neutrosophic multisets environment, the lower and upper approximation was a concerned property to study in explaining the roughness of the information needed. Meanwhile, the vectorial models of information which are cosine measure and dice measure represent the result for the similarity measure of rough neutrosophic multisets. The finding of this set theory gives a new generalization about similarity measure for multiple information involving indeterminacy information in the same environment. Besides that, the rough neutrosophic multisets theory also applicable set-in decision making for medical diagnosis. The comparison result showed that the roughness approximation of information is essential to get the best result in a close similarity measure.