Multi-criteria linguistic interval group decision-making approach

For group decision-making problems with linguistic assessment information, a new method based on two-tuple and WC-OWA operator is proposed, in which the criteria＇s weights and the decision-makers＇ preference information might take the form of linguistic grade, or might be between two continuous linguistic grades, or might be linguistic interval, or might be default. In this method, all linguistic values are transformed into two-tuple, and an aggregative decision-making matrix is obtained by using interval operation. The group aggregative values of each criterion on alternatives are computed by using a WC-OWA operator, the aggregative values on alternatives are worked out, and transformed into two-tuple. And the rank of the alternatives is obtained by using the order property of two-tuple. An example shows the feasibility and effectiveness of the proposed method.

Interactive group decision making procedure based on uncertain multiplicative linguistic preference relations

Group decision making problems are investigated with uncertain multiplicative linguistic preference relations.An unbalanced multiplicative linguistic label set is introduced,which can be used by the experts to express their linguistic preference information over alternatives.The uncertain linguistic weighted geometric mean operator is utilized to aggregate all the individual uncertain multiplicative linguistic preference relations into a collective one,and then a simple approach is developed to determine the experts＇ weights by utilizing the consensus degrees among the individual uncertain multiplicative linguistic preference relations and the collective uncertain multiplicative linguistic preference relations.Furthermore,a practical interactive procedure for group decision making is proposed based on uncertain multiplicative linguistic preference relations,in which a possibility degree formula and a complementary matrix are used to rank the given alternatives.Finally,the proposed procedure is applied to solve the group decision making problem of a manufacturing company searching the best global supplier for one of its most critical parts used in assembling process.

Fuzzy interval linguistic sets with applications in multi-attribute group decision making

Uncertain and hesitant information, widely existing in the real-world qualitative decision making problems, brings great challenges to decision makers. Hesitant fuzzy linguistic term sets(HFLTSs), an effective linguistic computational tool in modeling and eliciting such information, have hence aroused many scholars’ interests and some extensions have been introduced recently.However, these methods are based on the discrete linguistic term framework with the limited expression domain, which actually depict qualitative information using several single values. Therefore,it is hard to ensure the integrity of the semantics representation and the accuracy of the computation results. To deal with this problem, a semantics basis framework called complete linguistic term set(CLTS) is designed, which adopts a separation structure of linguistic scale and expression domain, enriching semantics representation of decision makers. On this basis the concept of fuzzy interval linguistic sets(FILSs) is put forward that employs the interval linguistic term with probability to increase the flexibility of eliciting and representing uncertain and hesitant qualitative information. For practical applications, a fuzzy interval linguistic technique for order preference by similarity to ideal solution(FILTOPSIS) method is developed to deal with multi-attribute group decision making(MAGDM) problems. Through the cases of movie and enterprise resource planning(ERP) system selection, the effectiveness and validity of the proposed method are illustrated.

Pythagorean Uncertain Linguistic Variable Hamy Mean Operator and Its Application to Multi-attribute Group Decision Making

Pythagorean fuzzy set(PFS) can provide more flexibility than intuitionistic fuzzy set(IFS) for handling uncertain information, and PFS has been increasingly used in multi-attribute decision making problems. This paper proposes a new multiattribute group decision making method based on Pythagorean uncertain linguistic variable Hamy mean(PULVHM) operator and VIKOR method. Firstly, we define operation rules and a new aggregation operator of Pythagorean uncertain linguistic variable(PULV) and explore some properties of the operator.Secondly, taking the decision makers' hesitation degree into account, a new score function is defined, and we further develop a new group decision making approach integrated with VIKOR method. Finally, an investment example is demonstrated to elaborate the validity of the proposed method. Sensibility analysis and comprehensive comparisons with another two methods are performed to show the stability and advantage of our method.

Some properties of linguistic preference relation and its ranking in group decision making

The group decision making problem with linguistic pref- erence relations is studied. The concept of additive consistent linguistic preference relation is defined, and then some properties of the additive consistent linguistic preference relation are studied. In order to rank the alternatives in the group decision making with the linguistic preference relations, the weighted average is first utilized to combine the group linguistic preference relations to one linguistic preference relation, and then the transformation function is proposed to transform the linguistic preference relation to the multiplicative preference relation, and thus the Saaty＇s eigenvec- tor method （EM） of multiplicative preference relation is utilized to rank the alternatives in group decision making with the linguistic preference relations. Finally, an illustrative numerical example is given to verify the proposed method. A comparative study to the linguistic ordered weighted averaging （LOWA） operator method is also demonstrated.

Multi-attribute group decision making method under 2-dimension uncertain linguistic variables

A method is proposed to deal with the uncertain multiple attribute group decision making problems,where 2-dimension uncertain linguistic variables(2DULVs)are used as the reliable way for the experts to express their fuzzy subjective evaluation information.Firstly,in order to measure the 2DULVs more accurately,a new method is proposed to compare two 2DULVs,called a score function,while a new function is defined to measure the distance between two 2DULVs.Secondly,two optimization models are established to determine the weight of experts and attributes based on the new distance formula and a weighted average operator is used to determine the comprehensive evaluation value of each alternative.Then,a score function is used to determine the ranking of the alternatives.Finally,the effectiveness of the proposed method is proved by an illustrated example.

Linguistic Single-Valued Neutrosophic Power Aggregation Operators and Their Applications to Group Decision-Making Problems

Linguistic single-valued neutrosophic set(LSVNS)is a more reliable tool,which is designed to handle the uncertainties of the situations involving the qualitative data.In the present manuscript,we introduce some power aggregation operators(AOs)for the LSVNSs,whose purpose is to diminish the influence of inevitable arguments about the decision-making process.For it,first we develop some averaging power operators,namely,linguistic single-valued neutrosophic(LSVN)power averaging,weighted average,ordered weighted average,and hybrid averaging AOs along with their desirable properties.Further,we extend it to the geometric power AOs for LSVNSs.Based on the proposed work;an approach to solve the group decision-making problems is given along with the numerical example.Finally,a comparative study and the validity tests are present to discuss the reliability of the proposed operators.

Dynamic hesitant fuzzy linguistic group decision-making from a reliability perspective

A dynamic hesitant fuzzy linguistic group decisionmaking(DHFLGDM) problem is studied from the perspective of information reliability based on the theory of hesitant fuzzy linguistic term sets(HFLTSs). First, an approach is applied to transform the dynamic HFLTSs(DHFLTSs) into a set of proportional linguistic terms to eliminate the time dimension. Second, expert reliability is measured by considering both group similarity and degree of certainty, and an optimization method is employed to quantify the linguistic terms by maximizing the group similarity. Third, through computing the attribute stability as well as its reliability, a combination rule which considers both reliability and weight is proposed to aggregate the information, and then the aggregated grade values and degree of stability are used to make a selection. Finally,the application and feasibility of the proposed method are verified through a case study and method comparison.

Some interval-valued intuitionistic uncertain linguistic hybrid Shapley operators

Two interval-valued intuitionistic uncertain linguistic hybrid operators cal ed the induced interval-valued intuitionistic uncertain linguistic hybrid Shapley averaging （I-IIULHSA） operator and the induced interval-valued intuitionistic uncertain linguistic hybrid Shapley geometric （I-IIULHSG） operator are defined. These operators not only reflect the importance of elements and their ordered positions, but also consider the correlations among elements and their ordered positions. Since the fuzzy measures are defined on the power set, it makes the problem exponentially complex. In order to simplify the complexity of solving a fuzzy measure, we further define the induced interval-valued intuitionistic uncertain linguistic hybrid λ-Shapley averaging （I-IIULHλSA） operator and the induced interval-valued intuitionistic uncertain linguistic hybrid λ-Shapley geometric （I-IIULHλSG） operator. Moreover, an approach for multi-attribute group decision making under the interval-valued intuitionistic uncertain linguistic environment is developed. Finally, a numerical example is provided to verify the developed procedure and demonstrate its practicality and feasibility.

Crowdsourcing-Based Framework for Teaching Quality Evaluation and Feedback Using Linguistic 2-Tuple

Crowdsourcing is widely used in various fields to collect goods and services from large participants.Evaluating teaching quality by collecting feedback from experts or students after class is not only delayed but also not accurate.In this paper,we present a crowdsourcing-based framework to evaluate teaching quality in the classroom using a weighted average operator to aggregate information from students’questionnaires described by linguistic 2-tuple terms.Then we define crowd grade based on similarity degree to distinguish contribution from different students and minimize the abnormal students’impact on the evaluation.The crowd grade would be updated at the end of each feedback so it can guarantee the evaluation accurately.Moreover,a simulated case is shown to illustrate how to apply this framework to assess teaching quality in the classroom.Finally,we developed a prototype and carried out some experiments on a series of real questionnaires and two sets of modified data.The results show that teachers can locate the weak points of teaching and furthermore to identify the abnormal students to improve the teaching quality.Meanwhile,our approach provides a strong tolerance for the abnormal student to make the evaluation more accurate.

Consensus model of social network group decision-making based on trust relationship among experts and expert reliability

Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.

新文科视野下高校中文专业语言类新型课程群建设研究

新文科建设对高校中文专业语言类课程群的交叉融合和系统协同提出了更高的要求。在深入剖析语言类课程设置现状基础上,提出新型课程群的核心理念及导向,基于此构建课程群模式,即基础知识层级、交叉素养层级和实践能力层级,进而提出建设跨学科教师团队、转变教学方法和教学理念、策划语言实践活动等具体实现路径。整体思路以培养能力复合型人才为导向,明确了系统性的知识结构串联、课程耦合和协同机制、多学科交叉融合等理念,为新文科背景下新型课程群建设和落地实践提供了有力支撑。

“乡音”未改:归侨的语言适应与群体认同——以泉州双阳华侨农场为例

论文以福建泉州双阳华侨农场为个案,以调研数据资料为基础分析了归侨回国后的语言适应和语言选择状况;语言作为文化最主要的载体,在归侨的集体记忆与身份认同方面发挥着重要的作用。华侨农场作为一种特殊的移民社区,语言生活多言多语并存。共同的侨居地生活和归国经历以及相同的侨居地语言,构建了归侨的群体认同。侨二代大多仍能熟练掌握父辈的侨居地语言,但工作和学习常用语以普通话和当地方言为主;侨三代的祖辈侨居地语言和方言水平则明显衰退,普通话是他们的常用语。归侨社区呈现“侨居地语言→本地方言→国家通用语言”的代际语言转移趋势。华侨农场的多元语言文化生态,是侨乡文化的特殊标签和宝贵资源。深入开展华侨农场语言生活调查,做好归侨社区语言规划、保护与传承侨乡语言资源,有利于深入挖掘侨乡特色语言文化,助推侨乡振兴及中国式现代化建设。

Linguistic neutrosophic matrix energy and its application in multiple criteria group decision-making

Matrix energy is an important representation tool of collective information.Then,it is not applied to various fuzzy and linguistic environments.To compensate for this gap,this article aims to extend the matrix energy to propose the energy of a linguistic neutrosophic matrix(LNM)for solving a multiple criteria group decision-making(MCGDM)problem,which fully contains LNMs of decisionmaker weights,criteria weights,and alternative evaluations.To realize the objective,this study first presents the energy of LNM in view of the true matrix energy,the false matrix energy,and the indeterminate matrix energy.Then,a MCGDM technique is established in view of the LNM energy method in a LNM circumstance.Finally,the developed MCGDM technique using the LNM energy is used to solve the hospital location choice problem in the full LNM scenario.Meanwhile,the decision results indicate the validity and usability of the established MCGDM technique.

AI-Enabled Grouping Bridgehead to Secure Penetration Topics of Metaverse

With the advent of the big data era,security issues in the context of artificial intelligence(AI)and data analysis are attracting research attention.In the metaverse,which will become a virtual asset in the future,users’communication,movement with characters,text elements,etc.,are required to integrate the real and virtual.However,they can be exposed to threats.Particularly,various hacker threats exist.For example,users’assets are exposed through notices and mail alerts regularly sent to users by operators.In the future,hacker threats will increase mainly due to naturally anonymous texts.Therefore,it is necessary to use the natural language processing technology of artificial intelligence,especially term frequency-inverse document frequency,word2vec,gated recurrent unit,recurrent neural network,and long-short term memory.Additionally,several application versions are used.Currently,research on tasks and performance for algorithm application is underway.We propose a grouping algorithm that focuses on securing various bridgehead strategies to secure topics for security and safety within the metaverse.The algorithm comprises three modules:extracting topics from attacks,managing dimensions,and performing grouping.Consequently,we create 24 topic-based models.Assuming normal and spam mail attacks to verify our algorithm,the accuracy of the previous application version was increased by∼0.4%-1.5%.

Group Decision-making Models on Determining the Importance Ratings of Technical Characteristics

Determining the importance ratings of technical characteristics is a typical group decision-making process. The linguistic-based approach can effectively manage the imprecise and multi-granularity information i;n quality function deployment and facilitate decision-making in deriving the importance ratings. Based on the linguistic weighted averaging （LWA） operator and the linguistic hybrid averaging （LHA） operator, a practical approach is proposed to first aggregate the individual judgments into a collective value for each technical characteristic under linguistic environment, and then measure the deviation degree of linguistic variables to obtain the importance ratings of technical characteristics. A case study shows the application of the proposed method.

基于直觉模糊语言集的直播带货窗口选择方法

商家利用职业直播带货主播推销产品已经成为当下最为火热的销售形式,本文利用基于直觉模糊语言集的群体多属性决策方法,为商家选择最优直播带货窗口提供了理论指导。在群体多属性决策方法的制定中,本文利用将语言变量转化为直觉模糊数的方式,对语言文本进行转化处理。分别考虑决策者与专家风险偏好的拟合程度,提出了一种将专家主观权重和客观权重相结合的专家权重确定方式。在对权重与直觉模糊集进行集合时,提出了一种全新的直觉模糊幂混合平均算子(IFPHA),并优化了集合过程中排序使用的得分函数。最后,采用topsis法,并结合改进的直觉模糊数相似度计算公式对最终方案进行了比较,选出最适合风险偏好中等商家的带货直播窗口。

考虑个性化语义和一致性的群体决策共识模型

本文针对专家给出语言偏好关系的群体决策问题,考虑不同专家语言术语的个性化语义和个体一致性,提出了一种群体决策共识模型。首先,基于一致性驱动的方法论确定专家语言术语的数值标度,将专家的个体语言偏好关系转化为模糊偏好关系,并通过计算个体模糊偏好关系与群体模糊偏好关系的相似度对群体共识度进行度量。为辅助不满足个体共识水平的专家调整其语言偏好关系,建立了考虑一致性控制的混合0-1线性规划模型来确定其语言偏好关系元素的调整范围。在此基础上,提出了考虑个性化语义和一致性控制的共识达成算法。最后,以在线教育平台选择问题为例说明了所提算法的可行性,并设计仿真实验验证了所提算法的有效性。实验结果表明,本文所提算法可以在保证个体一致性不被破坏的前提下提升群体共识水平。

基于HFLTS中融合专家权重的群决策模型

针对犹豫模糊语言术语集多属性群决策(HFLTSMAGDM)问题,从平面坐标的角度出发建立了一类决策模型.在犹豫模糊语言术语集(HFLTS)中添加决策专家权重,进而构建一种加权的犹豫模糊语言术语集(WHFLTS);将WHFLTS转换为加权的区间值犹豫模糊集(WIVHFS),并对WIVHFS中的区间数(IN)进行测度,把IN的测度结果与其对应的决策专家权重以平面点坐标形式进行描述,在此基础上建立了2个犹豫模糊元(HFE)的大小比较规则及度量2个HFE的距离模型;分别定义了计算属性的整体权重、个体权重以及综合权重的计算方法,在属性的不同权重类别下皆采用Maclaurin对称平均算子集结HFE以获取各方案的综合属性值.案例分析表明,将WHFLTS转换为加权的犹豫模糊集并以平面坐标形式书写而建立的决策算法是可行的,且决策模型具有很好的稳定性.

基于群决策的带决策时间窗竞争匹配问题的决策组织优化

针对共享资源匹配中个体决策方案未考虑个体决策相互影响且不稳定,导致决策竞争和产生决策失效的问题,基于决策时间窗内相互影响的个体决策实质为群决策的特征,引入群决策理论,将各个体决策竞争者视为有效决策的群决策成员,构建了资源匹配中关于决策时间点选择的群决策模型。以各个体决策的组合为群决策备选方案,考虑到决策过程时间因素对决策者心理行为的影响,建立了心理偏好系数描述不同时间点的决策者对属性偏好的程度,以此修正决策信息、优化决策。基于概率语言术语集(PLTSs)以概率形式融合语言评价信息和数值评价信息,并结合心理偏好系数给出了评价值的概率计算公式。最后将评价值概率集合与逼近理想解排序法(TOPSIS)结合,对各决策方案排序,求出群体共识下的最优决策方案,该决策方案为所有决策者的最佳决策时间点集合。以物流信息平台中的车找货为例验证了模型的有效性。所提出的方法可为平台解决匹配竞争而实施决策控制以及资源调度提供方向。