Hybrid vector similarity measures and their applications to multi-attribute decision making under neutrosophic environment

Abstract

In this paper, we propose new vector similarity measures of single valued and interval neutrosophic sets by hybridizing the concepts of Dice and cosine similarity measures. We present their applications in multi attribute decision making under neutrosophic environment. We use these similarity measures to find out the best alternative by determining the similarity measure values between the ideal alternative and each alternative. The results of the proposed similarity measures have been validated by comparing with other existing similarity measures reported in the literature for multi attribute decision making. The main thrust of the proposed similarity measures will be in the field of practical decision making, medical diagnosis, pattern recognition, data mining, clustering analysis, etc.

Three-way fuzzy concept lattice representation using neutrosophic set

“…a food company. This derived analysis from the proposed method is in good agreement with hybrid vector similarity method [31]. Moreover the proposed method provides rigorous analysis based on each parameter using the generated three-way fuzzy concepts.…”

“…Further it provides hierarchical ordering among them within complexity Oð2 m à 3nÞ. We can believe that the proposed method will be helpful in various research fields for multi-criteria decision making process [31], three-way decision making process [21] and incomplete context [15].…”

“…Let us suppose X be a space of points (objects) then a neutrosophic set N can be characterized by truth-membership function (T X ðNÞ), an indeterminacy function (I X ðNÞ), and a false membership function (F X ðNÞ) [26]. Further some related properties like complex neutrosophic set [27], shadow set [28], neutrosophic logic [29], neutrosophic graph [30], its partial ordering based on hesitant fuzzy sets [21] as well as its applications [31], in multi-criteria decision making process [32] are explored. Some other methods like fuzziness based classifier [33], fuzzy entropy [34], fuzzy decision tree [35], fuzzy based ensemble learning [36] and granular computing [18] is also studied.…”

NC-TODIM-Based MAGDM under a Neutrosophic Cubic Set Environment

“…On comparing with the existing neutrosophic decision making strategies [26][27][28][29][33][34][35][64][65][66][67][68][69], we see that the decision information used in the proposed NC-TODIM strategy is NC numbers, which comprises of interval neutrosophic information and single-valued neutrosophic information simultaneously; whereas the decision information in the existing literature is either SVNSs or INSs. Since NC numbers comprises of much more information, the NC numbers based on the TODIM strategy proposed in this paper is more elegant, typical and more general in applications, while the existing neutrosophic decision-making strategies cannot deal with the NC number decision-making problem developed in this paper.…”

Neutrosophic soft set decision making for stock trending analysis

“…Ye (2015) introduced a philosophy for tackling multi-trait decision-making issues with SVN-numbers. Pramanik et al (2017) proposed new vector similitude measures of single valued and interval NSs by hybridizing the ideas of Dice and cosine closeness measures. Mostly often, we see that data lack exactness, lack accuracy of expression.…”