New Multiparametric Similarity Measure And Distance Measure For Interval Neutrosophic Set With Iot Industry Evaluation

In the epoch of Internet of Things (IoT), we are confronted five challenges (Connectivity, Value, Security, Telepresence and Intelligence) with complex structures. IoT industry decision making is critically important for countries or societies to enhance the effectiveness and validity of leadership, which can greatly accelerate industrialized and large-scale development. In the case of IoT industry decision evaluation, the essential problem arises serious incompleteness, impreciseness, subjectivity and incertitude. Interval neutrosophic set (INS), disposing the indeterminacy portrayed by truth membership T, indeterminacy membership I, and falsity membership F with interval form, is a more viable and effective means to seize indeterminacy.

Employing the concept and function of tangency with similarity measures and counterpart distances for reliable medical consultations has been extensively studied in the past decades and results in lots of isomorphic measures for application. We compared the majority of such isomorphic measures proposed by various researchers and classified them into (a) maximum norm and (b) one-norm categories. Moreover, we found that previous researchers used monotonic functions to transform an identity function and resulted in complicated expressions. In this study, we provide a theoretical foundation to explain the isomorphic nature of a newer measure proposed by the following research paper against its studied existing one in deriving the same pattern recognition results. Specifically, this study initially proposes two similarity measures using maximum norm, arithmetic mean, and aggregation operators and followed by a detailed discussion on their mathematical characteristics. Subsequently, a simplified version of such measures is presented for easy application. This study completely covers two previous methods to point out that the complex approaches used were unnecessary. The findings will help physicians, patients, and their family members to obtain a proper medical diagnosis during multiple examinations.

Presents the use of fuzzy logic as a logic and as an uncertainty theory in the decision-making context Discusses the development of the TOPSIS method in classical and fuzzy context Justifies the use of fuzzy logic as an uncertainty theory Provides illustrative examples for each fuzzy TOPSIS extension Includes related MATLAB codes and case studies

Decision-making activities are prevalent in human life. Many methods have been developed to address real-world decision problems. In some practical situations, decision-makers prefer to provide their evaluations over a set of criteria and weights.

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In this paper we proposed a new distance and several similarity measures between interval neutrosophic sets.

The simplified neutrosophic set (SNS) is a generalization of fuzzy set that is designed for some practical situations in which each element has truth membership function, indeterminacy membership function and falsity membership function.