Hybrid Vector Similarity Measure Of Single Valued Refined Neutrosophic Sets To Multi Attribute Decision Making Problems
Download Hybrid Vector Similarity Measure Of Single Valued Refined Neutrosophic Sets To Multi Attribute Decision Making Problems PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Hybrid Vector Similarity Measure Of Single Valued Refined Neutrosophic Sets To Multi Attribute Decision Making Problems book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Hybrid vector similarity measure of single valued refined neutrosophic sets to multi-attribute decision making problems
This paper proposes hybrid vector similarity measures under single valued refined neutrosophic sets and proves some of its basic properties. The proposed similarity measure is then applied for solving multiple attribute decision making problems. Lastly, a numerical example of medical diagnosis is given on the basis of the proposed hybrid similarity measures and the results are compared with the results of other existing methods to validate the applicability, simplicity and effectiveness of the proposed method.
Refined Simplified Neutrosophic Similarity Measures Based on Trigonometric Function and Their Application in Construction Project Decision Making
Refined simplified neutrosophic sets (RSNSs) are appropriately used in decision-making problems with sub-attributes considering their truth components, indeterminacy components and falsity components independently. This paper presents the similarity measures of RSNSs based on tangent and cotangent functions. When the weights of each element/attribute and each sub-element/sub-attribute in RSNSs are considered according to their importance, we propose the weighted similarity measures of RSNSs and their multiple attribute decision-making (MADM) method with RSNS information. In the MADM process, the developed method gives the ranking order and the best selection of alternatives by getting the weighted similarity measure values between alternatives and the ideal solution according to the given attribute weights and sub-attribute weights. Then, an illustrative MADM example in a construction project with RSNS information is presented to show the effectiveness and feasibility of the proposed MADM method under RSNS environments. This study extends existing methods and provides a new way for the refined simplified neutrosophic MADM problems containing both the attribute weight and the sub-attribute weights.
New Similarity Measures of Single-Valued Neutrosophic Multisets Based on the Decomposition Theorem and Its Application in Medical Diagnosis
Cut sets, decomposition theorem and representation theorem have a great influence on the realization of the transformation of fuzzy sets and classical sets, and the single-valued neutrosophic multisets (SVNMSs) as the generalization of fuzzy sets, which cut sets, decomposition theorem and representation theorem have the similar effects, so they need to be studied in depth. In this paper, the decomposition theorem, representation theorem and the application of a new similarity measures of SVNMSs are studied by using theoretical analysis and calculations. The following are the main results: (1) The notions, operation and operational properties of the cut sets and strong cut sets of SVNMSs are introduced and discussed; (2) The decomposition theorem and representation theorem of SVNMSs are established and rigorously proved.