The Internet of Vehicles (IoV), as the cornerstone of intelligent transportation systems, is gradually attracting attention and accumulated a large amount of literature. Therefore, this article employs citation analysis and topic analysis to analyze the research in the IoV field, revealing the knowledge evolution trajectory and development dynamics. The study selects 10 909 documents from the Web of Science core collection. Through main path analysis, the study identifies the knowledge trajectory of “from Intelligent transportation technology to agent and communication technology to blockchain and security.” In topic analysis, important topics, such as machine learning, autonomous vehicles, simulation, security, and smart cities are identified. Meanwhile, three topic areas machine learning and traffic prediction, simulation and autonomous vehicles, and security and road vehicles are obtained. Our research not only contribute to the advancement of academic research in the IoV field but also provide significant references for the innovation and development of related industries.

Since the International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems published its first issue in 1993, it has made important contributions to the research field of computer science. In this study, based on the dataset of the publications published in this journal between 1993 and 2016 retrieved from Web of Science, a general overview of this journal is performed using bibliometric methods and visualized networks. First, the productive and influential publications, authors, institutions, countries/territories, and supraregions are analysed based on the total number of citations, publications, and different citation thresholds. Second, network visualization analysis is applied to illustrate the links and connections between terms by using the VOSviewer software. Moreover, the most cited journals and common author keywords of three continents, including North America, Europe, and Asia, are also presented. This paper will hopefully help researchers understand the research patterns of this journal.

TheIEEE Transactions on Fuzzy Systems(TFS) is a reputable international journal in the research domain of computer science and engineering. This study surveys the TFS publications between 1994 and 2015 which are indexed in Web of Sciences. The purpose is to present a comprehensive overview of the main influencing factors that affect the journal and identify the theme and citation structures of TFS. First of all, the publication and general citation structure of the journal as well as the most cited articles are analyzed. Then, the TFS authorship and coauthorship are well investigated, the maps of author cocitation network and representative subnetwork of the TFS coauthorship are presented. Next, this study gives a global overview of TFS publications. The most influential and productive countries/territories as well as the temporal analysis of the leading countries/territories are presented. Finally, the cocitation network for exploring the ground-breaking research is generated and the main cocitation clusters of TFS publications are discovered.

Ordered weighted averaging (OWA) operator has been received increasingly widespread interest since its appearance in 1988. Recently, a topic search with the keywords “ordered weighted averaging operator” or “OWA operator” on Web of Science (WOS) found 1231 documents. As the publications about OWA operator increase rapidly, thus a scientometric analysis of this research field and discovery of its knowledge domain becomes very important and necessary. This paper studies the publications about OWA operator between 1988 and 2015, and it is based on 1213 bibliographic records obtained by using topic search from WOS. The disciplinary distribution, most cited papers, influential journals, as well as influential authors are analyzed through citation and cocitation analysis. The emerging trends in OWA operator research are explored by keywords and references burst detection analysis. The research methods and results in this paper are meaningful for researchers associated with OWA operator field to understand the knowledge domain and establish their own future research direction.

Network information system security has become a global issue since it is related to the economic development and national security. Information system security assessment plays an important role in the development of security solutions. Aiming at this issue, a dual hesitant fuzzy (DHF) group decision-making (GDM) method was proposed in this paper to assist the assessment of network information system security. A systemic index containing four aspects was established including organization security, management security, technical security, and personnel management security. The DHF group evaluation matrix was constructed based on the individual evaluation information from each expert. Some power average operator–based DHF information aggregation operators are proposed and used to fusion the performance of each criterion for information systems. The advantage of these operators is that they can describe the relationship between the indexes quantitatively. Finally, a case study about information systems security assessment was presented to verify the effectiveness of proposed GDM methods.

The main focus of this paper is to investigate group decision-making (GDM) method under interval-valued multiplicative intuitionistic fuzzy environment based on Archimedean t-conorm and t-norm. First of all, some operations laws are proposed for interval-valued multiplicative intuitionistic fuzzy elements, which is an extension of multiplicative intuitionistic fuzzy operations developed earlier by other scholars. The effectiveness of these proposed operations is illustrated with some numerical examples. Then, a series of aggregation operators are proposed and the desirable properties are also studied. This paper reveals that some existing multiplicative intuitionistic fuzzy and interval-valued multiplicative intuitionistic fuzzy aggregation operators are the special cases of the operators proposed in this paper. Finally, a GDM method based on proposed operators under interval-valued multiplicative intuitionistic fuzzy environment is proposed, and a real case about annual evaluation for personnel of Zhejiang University of Finance and Economics is presented to illustrate the effectiveness of the proposed method.

Many information fusion methods have been widely investigated to tackle group decision making (GDM) problem under dual hesitant fuzzy (DHF) environment. Nevertheless, traditional DHF information fusion methods are not quite perfect and they could be improved. In this study, we introduce the Archimedean t-conorm and t-norm (ATT) to DHF environment. We first introduce the ATT operations for DHF information, some existing operations are proved to be the exceptional cases of the proposed ones. Then, several new aggregation operators for DHF information are proposed based on ATT operations. Finally, an actual case about the selection of cooperative hospital as an emergency hospital for a company is studied based on the proposed methods.

The performance and development review (PADR) evaluation in a company is a complex group decision-making problem that is influenced by multiple and conflicting objectives. The complexity of the PADR evaluation problem is often due to the difficulties in determining the degrees of an alternative that satisfies the criteria. In this paper, we present a hesitant fuzzy multiple criteria group decision-making methods for PADR evaluation. We first develop some operations based on Einstein operations. Then, we proposed some aggregation operators to aggregate hesitant fuzzy elements and the relationship between our proposed operators and the existing ones are discussed in detail. Furthermore, the procedure of multicriteria group decision making based on the proposed operators is given under hesitant fuzzy environment. Finally, a practical example about PADR evaluation in a company is provided to illustrate the developed method.

Information aggregation has been investigated and applied to many fields. This paper focuses on geometric aggregation operators under dual hesitant fuzzy environment. We develop some new geometric aggregation operators, such as the generalized dual hesitant fuzzy weighted geometric (GDHFWG) operator, the generalized dual hesitant fuzzy ordered weighted geometric (GDHFOWG) operator and the generalized dual hesitant fuzzy hybrid geometric (GDHFHG) operator. Some numerical examples are given to illustrate the developed operators. Finally, we give an application of our proposed operators to multi-criteria decision making with dual hesitant fuzzy information, a real decision making problem about human resource generalist selection is forwarded to show the effectiveness of our proposed method.

In this article, we examine the issue of triangular intuitionistic fuzzy information fusion. We first propose some new triangular intuitionistic fuzzy aggregation operators based on the prioritized average operator, such as the triangular intuitionistic fuzzy prioritized weighted average and the triangular intuitionistic fuzzy prioritized weighted geometric operators. We study some desired properties of the proposed operators, such as idempotency, noncompensatory, and boundary. We then develop an approach to deal with group decision-making problems under triangular intuitionistic fuzzy environments. Finally, a practical example about teaching quality evalution is provided to illustrate the group decision-making process.

Intuitionistic fuzzy set was studied by many authors because it is a powerful technique to depict uncertainty, which is a set containing three functions: the membership function; the nonmembership function; and the hesitancy function. The aggregation of intuitionistic fuzzy values (IFVs) is of paramount importance in decision making. In this paper, we research IFVs aggregation problems, where there exist a prioritization relationship over the aggregated arguments. First, we propose the generalized intuitionistic fuzzy prioritized weighted geometric operator based on Archimedean t-conorm and t-norm. Then, some of its desirable properties and special cases are investigated in detail. Furthermore, a multicriteria group decision-making problems is formulated with IFVs using the proposed operator. Finally, the validity and applicability of the proposed method, as well as analysis of the comparison with different generator functions, are illustrated with a real example about talent introduction. © 2012 Wiley Periodicals, Inc.