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This paper is a combination of time neutrosophic soft sets and Q- neutrosophic soft expert sets. We define the general concept of time Q-neutrosophic soft expert sets and study its properties. Some operations such as complement, union, and intersection are explored. Then a hypothetical application of this concept in the decision-making problem is given. [ABSTRACT FROM AUTHOR]

We establish the hybrid concept of complex bipolar- valued neutrosophic soft set (CBVNSS) as a hybrid model of bipolar neutrosophic soft set (BNSS)and complex fuzzy set (CFS). A CBVNSS is highly suitable for use in real life situations where the decision makers are interested to deal with bipolarity as well as truth membership, indeterminacy membership and falsity membership grades to the alternatives in an extended range with complex numbers. Certain operations on CBVNSS like complement, subset, union and intersection operations are defined. Some related examples are also given to enhance the understanding of the proposed concept. The basic properties are also verified. We then provide a decision-making method on the CBVNSS. Finally, a numerical example has been presented to verify validity and feasibility of the developed method. [ABSTRACT FROM AUTHOR]

The aim of this paper is to correct the assertions (3) and (4) of Proposition 5.2 proposed by Alkhazaleh [Journal of Intelligent and Fuzzy Systems 30 (2016) 1087-1098]. Every notions involved are extend to the arbitrary set case in a clear, rigorous, and non-burdensome manner. A counterexample illustrates the flaw of the assertions. We introduce some new notions describing 'subset' of time-neutrosophic soft sets (T-NSSs for short) and 'equal' of T-NSSs, and give some examples and related propositions. Then we use these results to remedy the flaw of the assertions, and to improve the work of Alkhazaleh. [ABSTRACT FROM AUTHOR]

In this paper as a generalization of neutrosophic soft set we introduce the concept of n-valued refined neutrosophic soft set and study some of its properties. We also, define its basic operations, complement, union intersection, "AND" and "OR" and study their properties. [ABSTRACT FROM AUTHOR]

In 2013 Ayman A. Hazaymeh in his PhD thesis introduced the concept of time-fuzzy soft set as a generalization of fuzzy soft set. In this paper and as a generalization of neutrosophic soft set we introduce the concept of time-neutrosophic soft set and study some of its properties. We also, define its basic operations, complement, union intersection, "AND" and "OR" and study their properties. Also, we give hypothetical application of this concept in decision making problems. [ABSTRACT FROM AUTHOR]

In 1993, Gau and Buehrer proposed the theory of vague sets as an extension of fuzzy set theory. Vague sets are regarded as a special case of context-dependent fuzzy sets. In 1995, Smarandache talked for the first time about neutrosophy, and he defined the neutrosophic set theory as a new mathematical tool for handling problems involving imprecise, indeterminacy, and inconsistent data. In this paper, we define the concept of a neutrosophic vague set as a combination of neutrosophic set and vague set. We also define and study the operations and properties of neutrosophic vague set and give some examples. [ABSTRACT FROM AUTHOR]

The basic aim of soft computing is to trade precision for a tractableness and reduction in solution cost by pushing the limits of tolerance for imprecision and uncertainty. This paper introduces a novel soft computing technique called complex neutrosophic relation (CNR) to evaluate the degree of interaction between two complex neutrosophic sets (CNSs). CNSs are used to represent two-dimensional information that are imprecise, uncertain, incomplete and indeterminate. The Cartesian product of CNSs and subsequently the complex neutrosophic relation is formally defined. This relation is generalised from a conventional single valued neutrosophic relation (SVNR), based on CNSs, where the ranges of values of CNR are extended to the unit circle in complex plane for its membership functions instead of [0, 1] as in the conventional SVNR. A new algorithm is created using a comparison matrix of the SVNR after mapping the complex membership functions from complex space to the real space. This algorithm is then applied to scrutinise the impact of some teaching strategies on the student performance and the time frame(phase) of the interaction between these two variables. The notion of inverse, complement and composition of CNRs along with some related theorems and properties are introduced. The performance and utility of the composition concept in real-life situations is also demonstrated. Then, we define the concepts of projection and cylindric extension for CNRs along with illustrative examples. Some interesting properties are also obtained. Finally, a comparison between different existing relations and CNR to show the ascendancy of our proposed CNR is provided. [ABSTRACT FROM AUTHOR]