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Low-carbon city (LCC) quality evaluation is getting increasingly attention in recent years. However, uncertainty decision-making processes and complicated indicators in LCC development have brought challenges to the evaluation, making it more difficult to reach a consensus during assessment. To address these issues, this study develops a novel comprehensive framework based technique for order of preference by similarity to ideal solution (TOPSIS) and Fermatean fuzzy hybrid weighted distance measure for LCC quality. Firstly, a new Fermatean fuzzy (FF) distance measure from hybrid weighted perspective, named as FF hybrid weighted distance (FFHWD) measured is proposed, and some of its merits and mathematical characteristics are also explored. An FFHWD–TOPSIS comprehensive evaluation framework is then presented, wherein the entropy model and best–worst method (BWM) are utilized to derive the weights of different indicators. In addition, based on the established LCC quality evaluation index system, the proposed FFHWD-TOPSIS approach is used to measure the level of development of LCC in five Chinese cities. Finally, a sensitivity and comparative analysis of the proposed framework are carried out in detail. This study not only contributes to enriching the evaluation index system for LCC development, but also to presenting researchers with a reference for scientific evaluation approach. [ABSTRACT FROM AUTHOR]

This paper presents the concept of a new hybrid model called spherical fuzzy N-soft expert sets, which is an extension of spherical fuzzy soft expert sets. The proposed model is highly suitable to describe the multinary data evaluation in terms of spherical fuzzy soft information considering multiple experts' opinions. Some fundamental properties, including subset, weak complement, spherical fuzzy complement, spherical fuzzy weak complement, union, intersection, AND operation, and OR operation, are discussed. Our proposed concepts are explained with detailed examples. An efficient algorithm is developed to solve multi-attribute group decision-making (MAGDM) problems. Further, to guarantee the high applicability scope and flexibility of our initiated framework, two real-world MAGDM problems, that is, predicting local election results using survey ratings before the election and ranking credibility of the smartphones using customer feedback, are solved. Finally, to endorse the accuracy and advantages of the proposed technique, a comprehensive comparative analysis of the presented approach with existing models such as spherical fuzzy soft expert sets and N-soft sets is provided. [ABSTRACT FROM AUTHOR]

The Industrial Internet of Things is crucial for enterprise and country to drive the strategic upgrade and raise the level of national intelligent manufacturing. When pondering the IIoT industry evaluation, the corresponding dominating issues involve numerous indeterminacies. Spherical fuzzy set, portrayed by memberships of positive, neutral and negative, is a more efficient methods of seizing indeterminacy. In this article, firstly, the fire-new spherical fuzzy score function is explored for solving some suspensive comparison issues. Moreover, the objective weight and combined weight are determined by Renyi entropy method and non-linear weighted comprehensive method, respectively. Later, the multi-criteria decision making method based on combined compromise solutionis developed under spherical fuzzy environment. Finally, the corresponding method is effectively validated by the issue of IIoT industry evaluation. The main characteristics of the presented algorithm are: (1) without counterintuitive phenomena; (2) no division or antilogarithm by zero problem; (3) no square root by negative number issue; (4) no violation of the original definition issue. [ABSTRACT FROM AUTHOR]

The CCN cache placement strategy is of great concern to optimize the energy consumption of the network, and provide better security and delivery efficiency. When considering the CCN cache placement strategy evaluation, the fundamental issues frequently involve great uncertainty. Intuitionistic fuzzy soft set, portrayed by the parameterized form of membership and nonmembership, is a more effectual pattern for seizing uncertainty. In this article, the comparison problem in intuitionistic fuzzy soft (IFS) environment is solved by new score function. Later, some novel properties of IFS matrix are explored in detail. In addition, the objective weight information is determined by CRITIC approach. At the same time, the combined weight is calculated by revealing concurrently subjective weight preference and the objective weight information. Then, IFS decision making method based CoCoSo (Combined Compromise Solution) is proposed. Finally, the effectiveness of the method is elaborated by CCN cache placement strategy selection, along with corresponding sensitivity analysis. The dominating traits of the explored algorithm are listed as follows: (1) have no counterintuitive phenomena; (2) without data requirements; (3) own strong discriminating ability. [ABSTRACT FROM AUTHOR]

The 5G industry is of great concern to countries to formulate a major national strategy for 5G planning, promote industrial upgrading, and accelerate their economic and technological modernization. When considering the 5G industry evaluation, the basic issues involve strong uncertainty. Pythagorean fuzzy sets, depicted by membership degree and non-membership degree, are a more resultful means for capturing uncertainty. In this paper, the comparison issue in Pythagorean fuzzy environment is disposed by proposing novel score function. Next, the ⊖ and ⊘ operations are defined and their properties are proved. Later, the objective weight is calculated by Criteria Importance Through Inter-criteria Correlation method. Meanwhile, the combined weight is determined by reflecting both subjective weight and the objective weight. Then, the Pythagorean fuzzy decision making algorithm based Combined Compromise Solution is developed. Lastly, the validity of algorithm is expounded by the 5G evaluation issue, along with their sensitivity analysis. The main advantages of proposed algorithm are: (1) have no counterintuitive phenomena; (2) without division or antilogarithm by zero problem; (3) own stronger ability to distinguish alternatives. [ABSTRACT FROM AUTHOR]

In the age of big data, we often face the huge Volume, high Velocity, rich Variety, accuracy Veracity and high Value (5Vs) with complicated structures. Big data industrial decision making is crucial for a country or society to improve the effectiveness of leadership, which can remarkably promote scale development and industrialization. Under such circumstance of big data industrial decision assessment, the intrinsic issue involves serious indeterminacy. Single-valued neutrosophic set, depicted by truth membership, indeterminacy membership and falsity membership, is a highly effective way to grasp uncertainty. The dominating aim is to explore multiparametric similarity measure and distance measure with their properties. Then, the objective weight is computed by deviation-based method and the combination weight is presented. Moreover, we propose a novel neutrosophic decision making method based on multiparametric similarity measure with combination weight, which is stated by a big data industry decision making issue, along with the impact of various parameters on the final ranking. In the end, a comparison between the proposed algorithm and some existing neutrosophic algorithms has been built by the antilogarithm by zero problem, counter-intuitive phenomena and division by zero problem for showing their validity. [ABSTRACT FROM AUTHOR]

Neutrosophic set, initiated by Smarandache, is a novel tool to deal with vagueness considering the truth-membership T, indeterminacy-membership I and falsity-membership F satisfying the condition 0 ≤ T + I + F ≤ 3 . It can be used to characterize the uncertain information more sufficiently and accurately than intuitionistic fuzzy set. Neutrosophic set has attracted great attention of many scholars that have been extended to new types and these extensions have been used in many areas such as aggregation operators, decision making, image processing, information measures, graph and algebraic structures. Because of such a growth, we present an overview on neutrosophic set with the aim of offering a clear perspective on the different concepts, tools and trends related to their extensions. A total of 137 neutrosophic set publication records from Web of Science are analyzed. Many interesting results with regard to the annual trends, the top players in terms of country level as well as institutional level, the publishing journals, the highly cited papers, and the research landscape are yielded and explained in-depth. The results indicate that some developing economics (such as China, India, Turkey) are quite active in neutrosophic set research. Moreover, the co-authorship analysis of the country and institution, the co-citation analysis of the journal, reference and author, and the co-occurrence analysis of the keywords are presented by VOSviewer software. [ABSTRACT FROM AUTHOR]

Pythagorean fuzzy set, generalized by Yager, is a new tool to deal with vagueness considering the membership grade μ and non-membership ν satisfying the condition μ 2 + ν 2 ≤ 1 . It can be used to characterize the uncertain information more sufficiently and accurately than intuitionistic fuzzy set. Pythagorean fuzzy set has attracted great attention of many scholars that have been extended to new types and these extensions have been used in many areas such as decision making, aggregation operators, and information measures. Because of such a growth, we present an overview on Pythagorean fuzzy set with aim of offering a clear perspective on the different concepts, tools and trends related to their extension. In particular, we provide two novel algorithms in decision making problems under Pythagorean fuzzy environment. It may be served as a foundation for developing more algorithms in decision making. [ABSTRACT FROM AUTHOR]