Zeshui Xu

Sichuan University | SCU · Business School

An intuitionistic fuzzy set, characterized by a membership function and a non-membership function, is a generalization of fuzzy set. In this paper, based on score function and accuracy function, we introduce a method for the comparison between two intuitionistic fuzzy values and then develop some aggregation operators, such as the intuitionistic fu...

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We study the multi-criteria decision making problems in which the information about preference values is expressed in the form of uncertain linguistic information. We introduce some operational laws of uncertain linguistic variables and the concept of the ideal point of preference values with uncertain linguistic information, and develop an uncerta...

In this paper, we study the fuzzy multi-attribute decision making problems with preference information on alternatives, in which the attribute values and the preference values given by the decision maker(s) are in the form of triangular fuzzy numbers, and the information about attribute weights is incomplete. We develop two approaches to solving fu...

In this paper, we present a class of new preference relations-dynamic fuzzy preference relations in which all the elements are the variables of time, and study some of their desirable properties. We also give a straightforward method for deriving the priority weights of dynamic fuzzy preference relations, and then develop an approach to constructin...

The existing probabilistic hesitant fuzzy decision-making methods are mostly based on discrete probability and seldom consider the continuity of probabilistic information of hesitant elements. Ignoring the continuity of probabilities is prone to distortion and loss of the original information. Continuous processing of the discrete probability infor...

The selection and utilization of different color spaces significantly impact the recognition performance of deep learning models in downstream tasks. Existing studies typically leverage image information from various color spaces through model integration or channel concatenation. However, these methods result in excessive model size and suboptimal...

Purpose This study aims to provide a comprehensive analysis of two-sided matching (TSM) research, an interdisciplinary field that integrates both theoretical and practical perspectives. By examining 756 research articles from the Web of Science database, this paper seeks to identify key trends, collaboration patterns and emerging research topics wi...

As an important measure to solve the multi-attribute decision-making (MADM) problems, the establishment of three-way decision (3WD) approach has been adopted not only stay at the theoretical level, but also applied to various practical problems. However, there exists a research gap of employing three-way decision (3WD) approach to enrich fault diag...

Dear Editor, This letter puts forward a novel scalable temporal dimension preserved tensor completion model based on orthogonal initialization for missing traffic data (MTD) imputation. The MTD imputation acts directly on accessing the traffic state, and affects the traffic management. However, it still faces the following challenges: 1) The MTD im...

In this paper, we propose a novel center-based clustering algorithm based on bidirectional conical information granularity. The main purpose is to fully absorb the semantic information of the ordinal relationship between objects to improve the performance of central clustering in identifying interleaved and imbalanced data. The proposed algorithm i...

Probabilistic hesitant fuzzy sets are an emerging and popular tool in the decision-making field, skilled at describing subjective information. However, it does not take into account the cognitive limitations of decision makers and the complexity of the actual environment can lead to situations such as multiple values or missing probabilistic inform...

Probabilistic hesitant fuzzy sets (PHFSs) (Zhu in Decision method for research and application based on preference relation, 2014.; Xu and Zhou in Fuzzy Optim Decis Making 16:1–23, 2016) use probabilistic information to express the importance of the membership degree, resulting in a more comprehensive representation of information in the PHFS. Howe...

China seeks the cooperation with the countries along the Belt and Road and has made great achievements in policy coordination, facilities connectivity, unimpeded trade, financial integration and people-to-people bond. However, there are also potential risks associated with these collaborations, which are closely related to the political conditions...

This section initially combines the probability theory to introduce the concept of continuous hesitant fuzzy element (CHFE). Following this, the concept of uniform hesitant fuzzy element (UHFE) is proposed, and discrete (probabilistic) hesitant fuzzy information is transferred to continuous one, benefitted from the connection between UHFEs and CHFE...

Probability theory and methods are commonly used in the process of information dissemination to describe propagation characteristics, predict development trends and provide guidance for final decision-making. When the information data is hesitant fuzzy set, due to its irregular form, many commonly used probability models may fail. In response to th...

In this chapter, we present several distribution-based weighting methods for hesitant fuzzy information and dual hesitant fuzzy information. The prominent characteristic of these methods is that they can reduce the influence of biased data, which obeys the majority rule. Finally, an example of a recruitment interview for a product manager has demon...

A multi-scale information system (MSIS) is a kind of information system that divides the data into different scales according to the thickness of different granularities, which solves the limitation of traditional single-scale information systems. In view of the importance on different data types of intervalvalues (IVs), intuitionistic fuzzy number...

Computational intelligence is increasingly applied to complex decision-making challenges, leveraging its data analysis prowess. Hybrid human-artificial intelligence models enhance the grasp of intricate social behaviors, offering valuable insights for social computing and behavior modeling. Within this landscape, large-scale group decision-making (...

As the deep learning algorithm, the long short-term memory (LSTM) network is an emerging and hot tool to address classification issues. In the classification process, to provide more reasonable suggestions, the subjective evaluation and qualitative selection given by decision makers and experts are important and cannot be ignored. Thus, this paper...

The COVID-19 outbreak has induced pivotal technological and socioeconomic changes, reshaping the global landscape. This meta-analytic review examines 52 studies from leading databases, offering a comprehensive insight into these profound shifts. The analysis highlights the acceleration in digital technologies adoption, encompassing remote work, e-c...

In some actual decision-making problems, experts may be hesitant to judge the performances of alternatives, which leads to experts providing decision matrices with incomplete information. However, most existing estimation methods for incomplete information in group decision-making (GDM) neglect the hesitant judgments of experts, possibly making the...

The multiple global environments have triggered changes in the international environment, leading to a sharp decline of foreign direct investment (FDI) compared to pre-pandemic level. To evaluate the investment risk of FDI and make optimal investment decision becomes the most important issue for investors. This paper focuses on the evaluation of in...

Social networks are gaining importance as an important application landscape for machine learning techniques. Currently, it is a prevalent thinking to introduce social networks into group decision-making (GMD) research, despite exhibiting promising performance, there remain significant challenges, including 1) trust risk is often overlooked, and 2)...

The Corona Virus Disease 2019 (COVID-19) epidemic has deferred global progress in energy efficiency to a decade-long low, posing a threat to the achievement of international climate goals, and also profoundly affected the development of economics. To gain insight into the research frontiers and hotspots in energy efficiency and COVID-19, a systemat...

Pythagorean fuzzy sets, as a generalization of intuitionistic fuzzy sets, have a wide range of applications in many fields including image recognition, data mining, decision making, etc. However, there is little research on clustering algorithms of Pythagorean fuzzy sets. In this paper, a novel clustering idea under Pythagorean fuzzy environment is...

In the group decision-making process, experts and decision makers can sometimes provide subjective evaluation information with classification labels. To effectively deal with it and make a reasonable decision, two key issues should be addressed first, which include the information representation and consensus classification model in the above uncer...

Workflow decision making is critical to performing many practical applications of scientific principles and data. Scheduling in edge-cloud environments can address the high complexity of workflow applications, while decreasing the data transmission delay between the cloud and end devices. However, due to the heterogeneous resources in edge-cloud en...

The aim of this paper is to investigate the multiple criteria group decision-making problem in which the evaluation values provided by experts construct some hesitant fuzzy numbers. We first analyze the characteristics of hesitant fuzzy number (HFN) and define the concept of feature vector of HFN. Then, applying the feature vectors of HFNs, some ne...

Intelligent Transportation Systems (ITSs) are designed to alleviate traffic congestion and provide convenience for travelers or decision-makers. However, the challenge lies in obtaining complete and accurate traffic data because of various factors. Therefore, many models have been studied for traffic data imputation. Most studies overlook the extre...

Traffic data prediction is a crucial component of Intelligent Transport Systems (ITS) as it contributes significantly to real-time navigation and congestion management. However, due to incomplete deployment of sensor and instability of data transmission, the traffic data that we collect is usually a high-dimensional and incomplete (HDI) matrix or t...

The new energy vehicle industry is thriving with high energy efficiency and environment friendly characteristic and how to select them is a significant comprehensive assessment problem. In the new energy vehicle assessment, the decision makers often encounter some qualitative evaluations which contain several adjacent linguistic terms, that is the...

The interpretability of prediction models is very important for decision management. The vast majority of existing prediction analysis models based on rough set theory lack a certain interpretability. To break through the existing framework, this paper deeply integrates rough fuzzy sets and logistic regression to construct an interpretable predicti...

Intelligent Transportation Systems (ITSs) are vital for alleviating traffic congestion and improving traffic efficiency. Due to the delay of network transmission and failure of detectors, massive missing traffic data are often produced in ITSs, which evidently decreases the accuracy of decision-making in road traffic management. Hence, how establis...

By comparing the attributes of objects one by one, an intuitionistic fuzzy relation, called the dominance-inferiority relation, is presented, and a dominance-inferiority-based rough set is introduced. Based on the dominance-inferiority relation and the dominance-inferiority-based rough set, the dominance-inferiority degree and dominance-inferiority...

The reforming and updating of power systems play a key role in promoting the low-carbon technology progress, saving non-renewable energy resources and reducing carbon emissions. The evaluation of power system reform proposals is an uncertain multiple-criteria decision-making problem given that some indicators cannot be represented by real numbers s...

The three-way decision theory provides a three-way philosophical thinking to solve problems, and the regret theory quantifies the risk preferences of decision makers under different psychological behaviors. On the one hand, the combination of these two theories makes models more practical by considering the psychological behaviors of decision maker...

Because of its outstanding performance, NAND flash memory in the form of embedded flash drives like Universal Flash Storage (UFS) has been widely used in the modern smartphones. As the core software in UFS, the flash translation layer (FTL) is essential to the performance improvement of UFS. To consider all workloads, a balanced and fixed mapping c...

In this paper, we propose a novel method for ranking fuzzy numbers based on additively consistent fuzzy preference relations (ACFPR). We introduce the so-called additive priority degree (APD) to capture pair-wise comparisons of fuzzy numbers. This measure is both separable by taking a suitable parameter in the weight function and able to induce an...

From the perspective of historical review, the methodology of economics develops from qualitative to quantitative, from a small sampling of data to a vast amount of data. Because of the superiority in learning inherent law and representative level, deep learning models assist in realizing intelligent decision-making in economics. After presenting s...

The strategy production in intuitionistic fuzzy multi-attribute decision-making is influenced by various factors. More realistic data representations are needed to portray ambiguity under increasingly complex decision-making contexts. Firstly, this study proposes a new approach for ranking independent trapezoidal intuitionistic fuzzy numbers based...

The notion of vehicle-to-everything (V2X) has been adopted and developed in a host of application scenarios due to its wide compatibility with intelligent transport, smart city or other relevant concepts since it was set forth. Benefiting from the application of advanced technologies, vehicles are connected with more and more objects, such as vehic...

Social trust network (STN) and minimum cost consensus (MCC) models have been widely used to address consensus issues in multi-attribute group decision-making (MAGDM) problems with limited resources. However, most researchers have overlooked the decision maker ‘(DMs)’ confidence levels (CLs) and adjustment willingness implicit in their evaluations....

In fuzzy large group decision making methods, an effective clustering method can greatly reduce the complexity of decision making, and it is an important ingredient for reaching a group consensus. In this paper, a novel fuzzy large group decision making method is established using three-way clustering and an adaptive exit-delegation mechanism. Trad...

Modern key-value (KV) storage systems adopt append-only writes to update KV pairs with the out-of-place manner, because the performance of sequential accesses is much better than that of random accesses for HDDs. Compaction or GC operations will be deployed by traditional KVs or KV separation schemes due to updating KV pairs via append-only writes....

In recent years, more and more attention is paid to the OWA operator in the academy. Growth curve analysis, which is often used in ecosystem studies, also indicates that this growth trend will continue. However, prior literature has not made a big picture to help researchers make clear of the development of this field by identifying the evolution p...

Plenty of online customer reviews (OCRs) provide consumers with an abundant source of word-of-mouth (WOM). It makes potential customers evaluate alternative products or services more conveniently. Thus, relative studies have been arising. Considering that existing research is almost deployed from the perspective of reviewers, the study proposes an...