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The idea of an interval complex neutrosophic soft set (I-CNSS) emerges from the interval neutrosophic soft set (I-NSS) by the extension of its three membership functions (T, I, F) from real space to complex space (unit disc) to better handle uncertainties, vagueness, indeterminacy, and imprecision of information in the periodic nature. The novelty of I-CNSS lies in its more significant range of activity compared to CNS. Measures of similarity and distance are important tools that can be used to solve many problems in real life. Hence, this paper presents some interval complex neutrosophic soft similarities based on Hamming and Euclidean distances of I-CNSSs to deal with real-life problems that include uncertain information such as decision-making issues and medical diagnosis stats. Firstly, this paper reviews the definition of an interval complex neutrosophic soft set. Secondly, we defined distance Hamming measures and distance Euclidean measures on I-CNSSs. Next, the axiomatic definition of similarity measures based on Hamming and Euclidean distances of I-CNSSs is proposed. Moreover, a numerical example is given and relations between these measures are introduced and verified. Meanwhile, some applications are given to show how similarity can be used to help the user in making decisions and making medical diagnoses. Finally, a comparison of some current approaches is used to back up this study. [ABSTRACT FROM AUTHOR]

In this paper, a new version of distance measure for hesitant fuzzy linguistic term sets is developed. The new version of distance measure provides an objective way to handle the diverse dimensions of two HFLTSs, i.e., without shortening the HFLTS to be a linguistic interval or extending the shorter one by adding linguistic terms. The Hamming distance, the Euclidean distance and the corresponding forms are put forward. By the relationship between the distance measure and the similarity measure, some parallel similarity measures are also investigated. As applications of the proposed measures, the issues of pattern recognition, clustering analysis and multi-criteria decision making are considered. [ABSTRACT FROM AUTHOR]

In this article we have introduced the concept of similarity measure for interval-valued intuitionistic fuzzy soft sets based on distance between two interval-valued intuitionistic fuzzy soft sets, some examples and basic properties are also studied. An algorithm is developed in intuitionistic fuzzy soft set setting for a decision making method. Lastly a fictitious numerical example is given to illustrate possible application in a medical diagnosis problem. [ABSTRACT FROM AUTHOR]

Molodtsov [35] initiated the soft set theory, which can be used as a generic mathematical tool for dealing with uncertainty. Maji [30] defined the concept of neutrosophic soft set which is based on a combination of the neutrosophic set and soft set models. In this paper, we give the notion of neutrosophic soft set with a new style and present some algebraic properties. We define several distance measures between neutrosophic soft sets and give an axiomatic definition of neutrosophic entropy for a neutrosophic soft set. To find the most ideal alternatives from all possible alternatives, we propose a method based on similarity measure. Thus we can rank all possible alternatives. Finally, the proposed similarity measure is applied to a multicriteria decision making problem. [ABSTRACT FROM AUTHOR]

Interval valued neutrosophic soft set introduced by Irfan Deli in 2014[8] is a generalization of neutrosophic set introduced by F. Smarandache in 1995[19], which can be used in real scientific and engineering applications. In this paper the Hamming and Euclidean distances between two interval valued neutrosophic soft sets (IVNS sets) are defined and similarity measures based on distances between two interval valued neutrosophic soft sets are proposed. Similarity measure based on set theoretic approach is also proposed. Some basic properties of similarity measures between two interval valued neutrosophic soft sets is also studied. A decision making method is established for interval valued neutrosophic soft set setting using similarity measures between IVNS sets. Finally an example is given to demonstrate the possible application of similarity measures in pattern recognition problems. [ABSTRACT FROM AUTHOR]

An interval neutrosophic set is an instance of a neutrosophic set, which can be used in real scientific and engineering applications. In the paper, the Hamming and Euclidean distances between interval neutrosophic sets (INSs) are defined and the similarity measures between INSs are proposed based on the relationship between similarity measures and distances. In the applications of the similarity measures, a multicriteria decision-making method is established in interval neutrosophic setting, in which criterion values with respect to alternatives are evaluated by the form of interval neutrosophic values (INVs) and the criterion weights are known information. We utilize the similarity measures between each alternative and the ideal alternative to rank the alternatives and to determine the best one. Finally, an illustrative example demonstrates the applications of the proposed decision-making method. [ABSTRACT FROM AUTHOR]

Soft set, as a parametrized family of subsets of a crisp universal set, has more ability to handle uncertain information. In this paper, we propose two types of similarity measure between soft sets and made a comparative study of these two techniques. Also we have shown an application of this similarity measure of soft sets. [ABSTRACT FROM AUTHOR]