Abstract
Based on dynamic information collected from different time intervals in some real situations, this paper firstly proposes a dynamic single valued neutrosophic multiset (DSVNM) to express dynamic information and operational relations of DSVNMs. Then, a correlation coefficient between DSVNMs and a weighted correlation coefficient between DSVNMs are presented to measure the correlation degrees between DSVNMs, and their properties are investigated. Based on the weighted correlation coefficient of DSVNMs, a multiple attribute decision-making method is established under a DSVNM environment, in which the evaluation values of alternatives with respect to attributes are collected from different time intervals and are represented by the form of DSVNMs. The ranking order of alternatives is performed through the weighted correlation coefficient between an alternative and the ideal alternative, which is considered by the attribute weights and the time weights, and thus the best one(s) can also be determined. Finally, a practical example shows the application of the proposed method.
Highlights
The theory of neutrosophic sets presented by Smarandache [1] is a powerful technique to handle incomplete, indeterminate and inconsistent information in the real world
As for some complex problems in real situations, such as some complex decision-making problems, moving image processing problems, complex medical diagnosis problems, and personnel dynamic examination, we have to consider these dynamic problems in different time intervals
Based on dynamic information collected from different time intervals in some real situations, this paper proposed a dynamic single valued neutrosophic multiset (DSVNM) to express dynamic information and the operational relations of DSVNMs
Summary
The theory of neutrosophic sets presented by Smarandache [1] is a powerful technique to handle incomplete, indeterminate and inconsistent information in the real world. As for some complex problems in real situations, such as some complex decision-making problems, moving image processing problems, complex medical diagnosis problems, and personnel dynamic examination, we have to consider these dynamic problems in different time intervals. In these cases, how can we express the dynamic problems? (1) to propose a dynamic single valued neutrosophic multiset (DSVNM) as a better tool for expressing dynamic information of dynamic problems; (2) to develop correlation coefficients between DSVNMs for measuring the correlation degree between two DSVNMs; and (3) to apply the correlation coefficient to multiple attribute decision-making problems with DSVNM information.
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