Decision-Making Method of Qualitative and Quantitative Comprehensive Evaluation of Talents Based on Probability Hesitation Fuzzy Language

A scientific, reasonable, and novel talent evaluation index system is the foundation of talent training and selection. Based on the novel “Man-Machine-Environment System Engineering” (hereinafter referred to as MMESE) theory, this paper proposes a novel talent evaluation index system that considers the ontological attributes and the external environment of the object comprehensively for talent evaluation, which could help the evaluator obtain more accurate evaluation results. Since the comprehensive evaluation of MMESE talents is a complex decision-making problem that is both qualitative and quantitative, a corresponding decision-making method that integrates qualitative and quantitative approaches is proposed here based on probabilistic language entropy and the possibility of superior order relationships. First, the weights of quantitative and qualitative attributes are calculated based on entropy theory and probabilistic fuzzy language. Second, the standard weight vectors of qualitative and quantitative attributes are obtained by adjusting the weight integration coefficients, and the change intervals of the pros and cons between the objects to be evaluated are calculated. Third, the pros and cons of the objects to be evaluated are compared to obtain the possibility degree matrix that describes the priority relationships among the objects, and a ranking vector is derived from the possibility degree matrix to reflect the rankings of the objects’ pros and cons. Finally, this system and the decision-making methods have been verified as scientific and effective.

Comprehensive Evaluation of Talent Growth Factor Index System Based on Hesitant Fuzzy Language

An effective evaluation of the index system of talent growth factors can lay a solid foundation to build the talent pool, as well as select and establish talents. In this study, based on the theory of “Man-Machine-Environment” system engineering (MMESE), the MMESE talent growth factor index system is proposed and verified for its effectiveness by comparing it with the traditional system. Based on the text-free grammar and transformation function, expert judgments of talent growth factor indexes were transformed into hesitation fuzzy language terms, namely, pertinence, systematicness, practicability, foresight, and dynamics, which were then used to create a dataset to describe the comprehensive evaluation of the index system. The entropy of hesitation fuzzy language terms adopts the algorithm, which calculates the index weights according to the relative entropy values and adjusts the expert weights with the expert group consensus model. The expert evaluation information was weighed and transformed into the corresponding probability language combination which was calculated as the comprehensive evaluation result of the talent growth factor index system.

Flexible Supplier Selection of WASPAS based on Hesitant Cloud Language

To ensure the continuity and stability of the supply chain under the sudden crisis, flexible supplier selection has taken up an important position in the operation decision of enterprises. Considering the differences of different expert decision-making and decision-making results that contain fuzziness, randomness and hesitation, the flexible supplier selection was studied by using the method of combining hesitant fuzzy language with normal cloud model and hesitant cloud linguistic term set was established. The weights were calculated according to the decision quality and aggregated with the evaluation results. Finally, WASPAS was used for scheme sorting to select the best supplier. The validity and applicability of the model were verified by a case study, which provided a scientific basis for enterprise decision makers to avoid interruption risk.

Minimization of Hesitant L-Fuzzy Automaton

In this paper, we study a new generalization for the notion of fuzzy automata, which we called hesitant L-fuzzy automaton (HLFA). We present the formulations of the mathematics framework for the theory of HLFA. Moreover, we present the concepts of hesitant L-fuzzy behavior and inverse hesitant L-fuzzy behavior recognized by a type of HLFA. After that, for any hesitant L-fuzzy language we present a minimal complete accessible deterministic hesitant L-fuzzy automaton recognizing that. Finally, we present an algorithm, which determines states of the minimal hesitant L-fuzzy automaton and we present the time complexity of the algorithm.

Research on Risk Assessment of Corporate Social Responsibility Based on Hesitant Fuzzy Language-Cloud Model

Risk of corporate social responsibility (CSR) refers to the possibility and consequences of the potential lack of CSR, which will cause damage and loss to society and enterprises. Hence, scientific evaluation of CSR risk is conducive to enterprises to take timely risk response measures and reduce potential risk factors. In order to fully reflect the CSR risk, a comprehensive risk evaluation index system is established from four dimensions of corporate stakeholders, law, environment and charity. In addition, hesitant fuzzy language is used to describe the CSR risk information, so as to reflect the uncertainty in the process of risk judgment. Considering the complexity of the CSR concept and the possible discreteness of risk results, the hesitant fuzzy language-cloud model is established to evaluate CSR risk level. Finally, utilizing China Huaneng Group as a case to apply the CSR risk evaluation model, it is found that the overall CSR risk level of Huaneng is relatively low. Through further comparative and hierarchical analysis, it is found that the CSR risk of community stakeholders is relatively high, and the CSR risk of legal, environmental and charitable is relatively balanced.

Extension of the TOPSIS Method for Decision-making Problem Under Dual Hesitant Fuzzy Language Environment

In order to comprehensively and actually describe the evaluation process, the dual hesitant fuzzy linguistic (DHFL) set is introduced in this paper, which includes more decision-making information, such as fuzzy state, hesitant process and language information. Specifically, some basic concepts of DHFL set are illustrated and a new distance measure for DHFL information is proposed, which is suitable for overcoming the irrational traditional methodology upon the general distance measure and basic probability concepts. Then, technique for order preference by similarity to ideal solution (TOPSIS) method is extended in dual hesitant fuzzy language environment, a novel TOPSIS method using the DHFL set is presented. Finally, the sensitivity analysis is performed to verify the feasibility and stability of the developed method, then the advantages of the proposed method are also confirmed by detailed comparative analysis.

Fuzzy Language Processing in Translation of Literature: A Case Study of Dr. Zha’s Diary of Fighting the COVID-19

Aesthetics is a subject focusing on studying the nature and significance of beauty (including beauty in language, art, literature, etc.). Moreover, the development of aesthetics, within the broader context of literary systems, is of significant importance. Chinese Literature (which in essence differs from that of English Literature) expresses beauty using its unique ways, especially with the employment of fuzzy language (also known as “vague language”). By including a certain degree of “fuzziness”, Chinese Literature grants readers room fir imagination. However, the process of translating Chinese fuzzy language into other languages is not an easy feat to accomplish. Such translations can, to a large extent, seriously affect the original meaning of the text. To explore proper ways of “fuzzy language” translation, this paper ventures to analyze the processing methods used in the translated work “Dr. Zha’s Diary of Fighting the COVID-19”. Categorizing vague language into three perspectives, namely, semantic vagueness, cultural vagueness and rhetorical vagueness, the paper analyzes the way to tackle fuzzy language with 16 detailed cases. Based on the case analyses, the paper proposes that the proper translation of fuzzy language in literature will be more conducive for readers to appreciate the works and helps to improve the translation quality. By exploring the ways of processing fuzzy language, this paper hopes to bring some suggestions and inspiration to other researchers.

Fuzzy Automata as Coalgebras

The coalgebraic method is of great significance to research in process algebra, modal logic, object-oriented design and component-based software engineering. In recent years, fuzzy control has been widely used in many fields, such as handwriting recognition and the control of robots or air conditioners. It is then an interesting topic to analyze the behavior of fuzzy automata from a coalgebraic point of view. This paper models different types of fuzzy automata as coalgebras with a monad structure capturing fuzzy behavior. Based on the coalgebraic models, we can define a notion of fuzzy language and consider several versions of bisimulation for fuzzy automata. A group of combinators is defined to compose fuzzy automata of two branches: state transition and output function. A case study illustrates the coalgebraic models proposed and their composition.

Cross-Docking Center Location Selection Based on Interval Multi-Granularity Multicriteria Group Decision-Making

Cross-docking is a new logistics model. The location planning of the crossover center is one of the important issues in logistics management. The location of the cross-docking center is not only a technical issue, but also a management issue. This is a decision made by senior leaders after considering various factors. Therefore, considering the decision-making method, a multicriteria group decision-making method based on an interval multi-granularity language model is proposed. It is suitable for non-static frameworks where the decision-making environment changes at any time during the process. Due to the uncertainty of the location information of the cross-docking center, experts can use their favorite language tag set to provide preferences, so a multi-granular interval fuzzy language model is used to enable experts to reliably provide preference values. At the same time, taking into account the formula threshold for decision-making, after a limited round of discussions, decision-making experts, site selection criteria, and site alternatives can be changed arbitrarily so that when the final opinion is reached, the consensus of experts reaches this threshold. Finally, through the numerical calculation of the site selection center, it is found that the experts will reach a higher level of consensus when joining the experts who change their status. The validity of the method is verified, and the feasibility and applicability of the proposed method are shown.

A Corpus-based Study of Shields in Conversations of Chinese EFL Learners

As an important part of the fuzzy language, hedges have become a common linguistic phenomenon and frequently applied in daily spoken language. In this study, the authors investigated the shields-using frequency of Chinese EFL learners from the Multi-modal Spoken English Corpus of Chinese Learners-Science & Engineering Majors (MSECCL-SEM). In this study, the classification of Prince et al. (1982) will be adopted. Six shields that are frequently used in spoken English have been searched, namely, “I think”, “in my opinion”, “maybe”, “according to”, “as we (all) know”, “it is said that”. Data are analyzed by the application of Wordsmith 6.0 and SPSS 25.0. Through this study, we attempt to explore the characteristics of shields in spoken English of EFL learners, especially the differences in terms of gender, various language proficiency and two different kinds of shields. Through this research, the authors hope to guide second language teaching and learning by finding out the use of shields in EFL students' daily spoken language and analyzing its potential causes.