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Abstract: In this paper, we discussed the feasibility of early recognition of highly cited papers with citation prediction tools. Because there are some noises in papers’ citation behaviors, the soft fuzzy rough set (SFRS), which is well robust to noises, is introduced in constructing the case-based classifier (CBC) for highly cited papers. After careful design that included: (a) feature reduction by SFRS; (b) case selection by the combination use of SFRS and the concept of case coverage; (c) reasoning by two classification techniques of case coverage based prediction and case score based prediction, this study demonstrates that the highly cited papers could be predicted by objectively assessed factors. It shows that features included the research capabilities of the first author, the papers’ quality and the reputation of journal are the most relevant predictors for highly cited papers. [Copyright &y& Elsevier]

Abstract: Advanced neuro-fuzzy modeling, namely an adaptive network-based fuzzy inference system (ANFIS), was employed to develop models for the prediction of suspended solids (SS) and chemical oxygen demand (COD) removal of a full-scale wastewater treatment plant treating process wastewaters from a paper mill. In order to improve the network performance, fuzzy subtractive clustering was used to identify model''s architecture and optimize fuzzy rule, meanwhile principal component analysis (PCA) was applied to reduce the input variable dimensionality. Input variables were reduced from six to four for COD and SS models, by considering PCA results and linear correlation matrices among input and output variables. The results indicate that reasonable forecasting and control performances have been achieved through the developed system. The minimum mean absolute percentage errors of 1.003% and 0.5161% for CODeff and SSeff could be achieved using ANFIS. The maximum correlation coefficient values for CODeff and SSeff were 0.9912 and 0.9882, respectively. The minimum mean square errors of 1.2883 and 0.0342, and the minimum RMSEs of 1.135 and 0.1849 for CODeff and SSeff could also be achieved. [Copyright &y& Elsevier]

Purpose: The current article presents the results of a case study dealing with the historical roots of Eastern European researchers in computer science. Design/methodology/approach: The study is based on an analysis of cited references stemming from a collection of around 80,000 computer science papers by Eastern European researchers published from 1989 to 2014. By using a method called "reference publication year spectroscopy" (RPYS) for historical analyses based on bibliometric data, we analyze around 800,000 references cited in those papers. The study identifies the peak years, including most frequently cited publications (from 1952, 1965 and 1975), and focuses on these outstanding works for the field. The research shows how these influential papers were cited in Eastern Europe and in general, and on which scientific fields they have the most impact. Findings: A noteworthy publication that seems to have a tremendous effect on Eastern European computer science is Zadeh's "Fuzzy sets" article which appeared in Information and Control in 1965. The study demonstrates that computer scientists from Eastern Europe are more conservative in their citation behaviour and tend to refer to older and more established research than their counterparts from the West. Originality/value: Which are the historical roots of researchers working in a particular field or on a specific topic? Are there certain publications – landmark papers – which are important for their research? We guess that these are questions bothering researchers in many fields. [ABSTRACT FROM AUTHOR]

This paper investigates the potential impact of green fuel adoption on the Saudi Arabian maritime industry using fuzzy set theory. We will examine the cost-profitability of green fuel adoption and its implications for the Saudi Arabian economy. By employing fuzzy set theory, we can more accurately predict and analyze the potential impacts of green shipping. This paper will present case studies from the shipping industry that have successfully used fuzzy set theory to optimize green fuel usage and profitability. Moreover, this paper will focus on the use of green fuels as a way of reducing the environmental impacts of the shipping industry in Saudi Arabia. This paper will explore the impact of fueling ships with green fuel in Saudi Arabia and use fuzzy set theory to analyze the cost-profitability of this action. [ABSTRACT FROM AUTHOR]

In a complex financial market, people pay more attention to the portfolio selection model in some fuzzy environment. Some properties and definitions of semivariance and entropy are given and proved in this paper. Then, the fuzzy tri-objective mean-semivariance-entropy portfolio model is proposed based on credibility theory when the return rates are fuzzy numbers. We present a novel layer-by-layer tolerance evaluation method to solve the proposed model in this paper. Finally, a numerical example is given to illustrate the effectiveness of the model and method proposed in this paper. There are two improvements in our proposed method: one is that the evaluation function idea is considered in the process of laying objective functions; the other is that the preference degree and subjective wills are presented by tolerant amounts of objective function values. [ABSTRACT FROM AUTHOR]

Fuzzy posets can be regarded as a generalization of classical posets. Many concepts and results in posets can be generalized to fuzzy posets. In order to further improve the fuzzy poset theory, in this paper, we shall introduce the concept of prime (distributive) fuzzy posets which can be seen as the correspondence of prime (distributive) posets in fuzzy setting. First, we consider the extensions of fuzzy ideals in a fuzzy poset. Then by the extensions of fuzzy ideals, we give a characterization for prime (distributive) fuzzy posets, that is, a fuzzy poset X is prime (distributive) if and only if all extensions of normal fuzzy ideals of X are Frink (strong) fuzzy ideals. This paper generalizes the work of Halas in posets into fuzzy posets. [ABSTRACT FROM AUTHOR]

The paper aims to describe a structured framework to implement, sustain and manage a quality-costing program in a process industry. After briefing about the advantages and disadvantages of various cost accounting approaches practiced by the industries, the authors described the need for attaching fuzziness to the notion of 'quality'. The proposed approach is discussed with the help of a case from paper industry. After obtaining expert elicitation, the imprecise, vague, and complex information related to quality cost items (under four key cost segments, i.e. prevention [P], appraisal [A], Internal failure [IF], and external failure [EF]) is synthesized using well-established principles of fuzzy set theory. To help the management in successful implementation of quality cost accounting system (QCAS) five alternatives for each cost category were considered. By obtaining the priority values with respect to various alternatives the implementation program was revived. The comparative analysis carried out after collecting the information under PAF cost segments showed a progressive and significant change in quality costs. [ABSTRACT FROM AUTHOR]

We propose a new concept which is a generalization of fuzzy soft subset and fuzzy soft equal. Using such notions, we will be able to consider the distributive law of fuzzy soft sets. Using the distributive law of fuzzy soft sets, we point out that the distributive law of trapezoidal fuzzy soft sets as proposed by Xiao et al. (2012) is not true. The correction will further improve further extensions of the results of Xiao et al. (2012). We will also establish the generalized distributive law of trapezoidal fuzzy soft sets along with illustrative examples. [ABSTRACT FROM AUTHOR]

Collection management is an important duty of librarians. In the last years journal prices have increased and library decision-makers have been forced to consider cancelling some journal subscriptions as budgets have not increased always by the same ratio. This fact has made it essential to supply reliable and efficient measures about the importance of different journals for in-house users in order to help the decision-makers to cancel subscriptions. Many journal-use studies can be found in the literature providing methods for making these kinds of decisions, but usually they consider only one single and precise decision criterion. Nevertheless, it is common knowledge that any real decision usually considers more than one criterion, and so the problem of choosing a set of journals to cancel is compounded by the existence of conflicting criteria, such as the cost of the journal and demand for the journal. As predicting possible number of users of a certain journal is a complex task, the expert''s judgments could be vital elements. Fuzzy Set theory could be a useful tool in dealing with these kinds of real decisions based on the expert''s knowledge and characterized by some level of subjectivity, in which the decision-maker has imprecise and/or vague data and/or incomplete information. In this paper a fuzzy bicriteria optimisation method is proposed to determine the optimal shape of the printed journal collection in a medical library in a Spanish public hospital. We jointly consider two criteria: maximising a usage function and also an opportunity coefficient of purchase function, both defined for each printed journal. Budget constraints and minimum availability constraints are taken into account. The proposed model is flexible, incorporates expert knowledge and can be easily extended to other hospital libraries. [Copyright &y& Elsevier]

In the recent era, Transportation considers the most powerful component of the business logistics system. Likewise, there is an interdependent relationship between the transportation and logistics systems. This paper aims to make a comparative study of logistics transportation problems based on intelligence algorithms. The researchers surveyed the previous studies conducted in the Artificial Intelligent field to solve complex problems. In this research study, the authors focused on techniques that are mostly applied in transportation and logistics systems, especially, Artificial Neural Network, Genetic Algorithm, and Fuzzy Logic models. Also, a proposed model and algorithm was done to obtain customers' and organizations' satisfaction. Artificial Neural Network uses as a decision tool that combines the system stat sets and the operation state-dependent sets. As well, the genetic algorithm combines the best parameters as a method to finds the best evaluation solutions. And fuzzy logic uses a fuzzy set to help decision-makers in making the best decisions in multiple fields. Finally, authors recommended to work in two new areas which are FGA, NFGA Algorithms to solve complex and multimodal problems that faces transportation logistics sector. [ABSTRACT FROM AUTHOR]

There are many schools of Chinese martial arts routines and complex movements; research on this topic is more geared toward Taijiquan (a kind of traditional Chinese shadow boxing), which is a more well-known type of martial arts. Therefore, the purpose of this paper is to visually analyze the research of Chinese martial arts routines based on the knowledge graph method and to propose a knowledge graph method based on the fuzzy set theory, which is called the transF model throughout this paper. The transF model used the fuzzy relational operation of vectors to not only reduce the computational complexity, but to also better integrate multi-dimensional data, especially when the training set is not particularly sufficient. For the visual analysis of Chinese martial arts routines, this paper selected the 16-year data from 2005 to 2020 as the analysis sample, analyzed high-yield institutions and high-yield authors, and conducted a centrality analysis of the whole dataset. From the structure of the knowledge graph, traditional martial arts are the core part of Chinese martial arts, with a centrality of 0.14. Competitive martial arts are the main branch of Chinese martial arts and the third core after Tai Chi and traditional martial arts, with a centrality of 0.41, which is higher than that of traditional martial arts. This shows its importance in martial arts research. [ABSTRACT FROM AUTHOR]

The design for large-scale offshore systems like renewable energy systems as well as ship structures represents the key factor for the investigation and application of such devices. The existing guide for design schemes of offshore systems cannot cover novel large-scale design demand for recent offshore systems, as a result of the fast-growing scale of offshore systems but the late update of guides. To this end, this paper proposes a novel risk estimation approach of alternative design schemes for large-scale offshore systems as a basis to support the design scheme determinations. Initially, the risks of design schemes are analyzed by fault tree analysis. Subsequently, Bayesian networks and fuzzy sets are employed to calculate the reliability of alternative designs that comply with, or deviate from, the existing guides. The risk level of alternative designs is assessed to ensure the better performance of alternative design schemes in terms of safety. The Bayesian network approach proposed also accretions the weak links in the alternative designs. The results of this paper contribute to enhancing the survivability of offshore systems, such as renewable energy systems as well as ship structures. [ABSTRACT FROM AUTHOR]

This brief paper addresses problems that were raised in the paper (Fuzzy Sets and Systems, this issue) in connection with modelling fuzzy equality and similarity. In addition to specific comments to the cited paper, we also point out the more fundamental questions underlying this discussion. [Copyright &y& Elsevier]

In our paper, we continue the study of the theory of fuzzy soft sets and their properties. Based on the singular values of the corresponding matrix, we define the energy of a fuzzy soft set, as well as the λ-energy of a fuzzy soft set, allowing us to introduce an effective method for decision-making. Then, we consider the limits of the defined energies, which are essentially non-negative numerical values. The paper demonstrates through examples how the introduced method can be successfully applied to many problems containing uncertainties. Additionally, the paper includes comparisons of the introduced method with other methods addressing similar problems. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy and society, the innovation of grassroots social governance has become increasingly important. This paper constructs 35 grassroots social governance innovation samples. Using the TOE theoretical framework and a fuzzy set qualitative comparative analysis (fsQCA), this paper analyzes the joint effects and interactive relationships of multiple factors on grassroots social governance innovation performance from three dimensions: technology, organization, and environment. The research reveals that internal environmental openness is a necessary condition for achieving high innovation performance in grassroots social governance, and proposes four grouping models that affect the performance of grassroots social governance innovation. This paper explores the inner logic of grassroots social governance innovation from a histological perspective, and on this basis proposes an adaptive path to enhance the performance of grassroots social governance innovation. [ABSTRACT FROM AUTHOR]

The concept of Hesitant Fuzzy Sets (HFS) came into picture where a set is created of the possible membership values that are willing to participate for contribution to the fuzzy sets. HFS has recently become very popular between researchers who are working on variants of fuzzy logic. This paper highlights the research queries related to the Scientometric analysis of HFS by studying 410 research publications from the Web of Science (v.5.31) database (from inception of Web of Science online data till 2017). This paper answers questions pertaining to the important terms and concepts for HFS, co-authorship patterns in HFS, dominating research areas of HFS, and countries with maximum research paper contribution, co-citation patterns for first authors and bibliographical coupling for organizations. A brief outline of the citation analysis is also made in the form of a sub-section. [ABSTRACT FROM AUTHOR]

The key objective of the present proposed work in this paper is introduced a new version of picture fuzzy set so called spherical fuzzy sets (SFS). spherical fuzzy set is a new extension of picture fuzzy sets and Pythagorean fuzzy sets. In spherical fuzzy sets, membership degrees are gratifying the condition 0 ⩽ P2 (x) + I2 (x) + N2 (x) ⩽1 instead of 0 ⩽ P (x) + I (x) + N (x) ⩽1 as is in picture fuzzy sets. In this paper, we investigate the basic operations of spherical fuzzy sets and discuss some related results. We extend operational laws to aggregation operators and introduce weighted averaging and weighted geometric aggregation operators based on spherical fuzzy number's. Further a multi attribute decision making method is developed and these aggregation operators are utilized. Finally, we constructed a numerical approach for implementation of proposed technique. [ABSTRACT FROM AUTHOR]

This paper discussed the fuzzy reliability of pulping system in paper industry. Pulping system consists of four subsystems such as Digester, Knotter, Deckers, and Openers. These subsystems are working in series. In subsystems Knotter and Openers, one unit is operative and another unit is kept as cold standby. Fuzzy failure rates and fuzzy repair rates of the subsystems are taken as general. Trapezoidal fuzzy numbers are used to find out the reliability of the pulping system. Using Mehar’s method, the numerical results for reliability are obtained by considering exponential, Rayleigh, and Weibull distributions. On the basis of the results obtained in this study, it is suggested that paper industry management should involve Weibull distributed random variables for pulping system to attain higher reliability. [ABSTRACT FROM AUTHOR]

Relieving the emotions of the public through government response is an important part of government emergency management. How governments respond in different situations can avoid stimulating negative emotions during emergencies? This paper analyzes the problem from the perspective of configuration; that is, this paper explores the combined effects of multiple factors on emotions. We construct the theoretical framework "Situation-Responder-Content" from situation, responder and response content, and use the government microblogs (n= 1517) from 23 major production accidents in China for the discussion with the use of fuzzy set qualitative comparison analysis (fsQCA). According to the results, the effective response types of different agencies in emergencies are summarized. Local authorities can respond in ways that include "Measures type" and "Measures-Emotion type". Functional agencies can respond through "Measures type", "Measures-Emotion type" and "Government feature-Driven" type. This study emphasizes that government response in emergencies is a systematic process. Responsive agencies need to release effective information on the basis of fully considering the situation and other factors. Configuration analysis should also be an important direction in government response research, which is helpful to the practice of government response in emergencies. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this note is to correct two convergence theorems for the generalized fuzzy integrals given in Fang [On the convergence theorems of generalized fuzzy integral sequence, Fuzzy Sets and Systems 124 (2001) 117–123]. [Copyright &y& Elsevier]

Paper " B Combinatorial design of the MAUT and PAMSSEM II methods for multiple attributes group decision making with probabilistic linguistic information b " looks at the use of probabilistic linguistic term sets in multiple attribute group decision making when the weights are unknown. The special issue focuses on various fuzzy summability techniques that are used in a variety of scientific, engineering, and technological fields. The guest editor wishes to express his heartfelt appreciation to Editors-in-Chief, Special Issue Editor, and other editorial staff members of "Soft Computing" for providing and supporting the opportunity to publish this special issue. Paper " B Cold start aware hybrid recommender system approach for E-commerce users b " proposes a methodological approach called sparsity and cold start aware hybrid recommended system (SCSHRS) to suppress data sparsity and cold start problems in the recommendation system. [Extracted from the article]

Debt restructuring is an effective means to solve the financial difficulties of enterprises. At present, the operation methods and means of enterprises with different characteristics to participate in debt restructuring are different, and no universal debt restructuring scheme has been formed. In order to solve this problem, this paper uses the method of fuzzy set qualitative comparative analysis. This paper discusses the influence mechanism of multiple concurrent factors on enterprise debt restructuring and summarizes the selection rules of debt restructuring strategies for enterprises with different characteristics of debt. The research shows that there are five kinds of allocation for enterprises to realize debt restructuring. According to the different core conditions, enterprise debt restructuring can be divided into high-quality operation and management mode, technology leading mode, and debt-to-equity mode. The research results reveal the mechanism behind enterprise debt restructuring and provide a reference basis for the government and creditors to make corresponding decisions in the debt restructuring process. [ABSTRACT FROM AUTHOR]

Infrastructure networks are critical components of contemporary society, and numerous approaches have been suggested for the selection of strategies to protect these networks. However, for uncertain environments, research on attack and defense game models for infrastructure networks is limited. Therefore, after reviewing the existing approaches, a method based on interval-valued intuitionistic fuzzy set (IVIFS) theory is proposed for attack and defense games in critical infrastructure networks. First, we present the process of constructing the game model proposed in this paper, which mainly includes the formulation of the cost model, the strategies, and the method of generating IVIFS payoffs. Next, the Nash equilibria of the game are identified by a pair of nonlinear programming models based on IVIFS theory. Finally, experiments are conducted on a target scale-free network, and an investigation into the variation patterns of the Nash equilibria under different circumstances is also conducted. We provide explanations for these variation patterns by considering payoffs from the perspective of mathematical programming models. Furthermore, we find that compared to the existing attack and defense game model with crisp payoffs, the model proposed in this paper leads to superior Nash equilibria. Our work is a preliminary attempt to analyse attack and defense games for infrastructure networks based on IVIFS theory, providing a method for assessing payoffs in uncertain environments for the attacker and defender. This topic deserves further study. [ABSTRACT FROM AUTHOR]

Zadeh introduced fuzzy sets to study imprecision in real life after which many variants of fuzzy sets have been developed in literature. In this paper, new variants of fuzzy sets named Hybrid fuzzy sets and Hybrid intuitionistic fuzzy sets have been defined based on some real life scenarios where conventional fuzzy sets are not applicable for dealing Multi-Criteria Decision Making (MCDM) problems. Further, total ordering algorithms on those proposed sets based on scoring functions are defined and applied in MCDM problems where decision matrix is incomplete with respect to some criteria. The major drawback of MCDM problems is non-availability / missing of data values for some alternatives with respect to some criteria while collecting data from the experts. To overcome this, researchers infuse the missing data for one expert from the corresponding data collected from the other expert or deleting that criteria to form a single complete MCDM table. But there are situations in which decisions should be taken with single MCDM matrix with missing data points. In this paper, we have proposed a new method in which we find the unknown data from known values / other entries of the table using relative performances of the alternatives with respect to other criteria through which we attain a ranking of the alternatives of MCDM using total ordering defined on the hybrid intuitionistic fuzzy sets. Further, we proposed another method in which we obtain the score of missing values based on the scores defined on the hybrid intuitionistic fuzzy sets through which final decision / ranking is made. Finally, the applicabilities of new types of fuzzy sets and total ordering methods are established in the field of Fuzzy decision making by comparing with existing imputation methods in the literature. [ABSTRACT FROM AUTHOR]

Fuzzy sets possess remarkable abilities in expressing and handling information uncertainty, which has resulted in their widespread application in various fields. Nevertheless, distance measurement between IFSs for quantitating their differences and levels of differentiation has remained an open problem that deserves attention. Despite the development of various metrics, they either lack intuitive insight or do not satisfy the axioms of distance measurement, leading to counterintuitive results. To address these issues, this paper proposed a distance measurement method based on Clark divergence, which satisfies the distance measurement axioms and exhibits nonlinearity. Numerical examples demonstrate that our method effectively distinguishes different indicators, yielding more reasonable results. Moreover, when comparing relative differences of the results, our method demonstrated superior adaptability to complex environmental decision-making, providing decision-makers with more accurate and confidential judgments. In our numerical and pattern classification application tests, we achieve an accuracy of 98%, a 40% increase in computing time efficiency and a relative diversity improvement of 35%. The pattern classification algorithm designed in this paper will offer a promising solution to inference problems. [ABSTRACT FROM AUTHOR]