Medical Diagnosis Based on Multi-Attribute Group Decision-Making Using Extension Fuzzy Sets,Aggregation Operators and Basic Uncertainty Information Granule

Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.

Novel combinatorial algorithm for the problems of fuzzy grey multi-attribute group decision making

To study the fuzzy and grey information in the problems of multi-attribute group decision making, the basic concepts of both fuzzy grey numbers and grey interval numbers are given firstly, then a new model of fuzzy grey multi-attribute group decision making based on the theories of fuzzy mathematics and grey system is presented. Furthermore, the grey interval relative degree and deviation degree is defined, and both the optimistic algorithm of the grey interval relational degree and the algorithm of deviation degree minimization for solving this new model are also given. Finally, a decision making example to demonstrate the feasibility and rationality of this new method is given, and the results by using these two algorithms are uniform.

Power Aggregation Operators of Simplified Neutrosophic Sets and Their Use in Multi-attribute Group Decision Making

The simplified neutrosophic set(SNS) is a useful generalization of the fuzzy set that is designed for some practical situations in which each element has different truth membership function, indeterminacy membership function and falsity membership function. In this paper, we develop a series of power aggregation operators called simplified neutrosophic number power weighted averaging(SNNPWA) operator, simplified neutrosophic number power weighted geometric(SNNPWG) operator, simplified neutrosophic number power ordered weighted averaging(SNNPOWA) operator and simplified neutrosophic number power ordered weighted geometric(SNNPOWG) operator. We present some useful properties of the operators and discuss the relationships among them. Moreover, an approach to multiattribute group decision making(MAGDM) within the framework of SNSs is developed by the above aggregation operators.Finally, a practical application of the developed approach to deal with the problem of investment is given, and the result shows that our approach is reasonable and effective in dealing with uncertain decision making problems.

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.

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.

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.

A Multi-Attribute Decision-Making Method Using Belief-Based Probabilistic Linguistic Term Sets and Its Application in Emergency Decision-Making

Probabilistic linguistic term sets(PLTSs)are an effective tool for expressing subjective human cognition that offer advantages in the field ofmulti-attribute decision-making(MADM).However,studies have found that PLTSs have lost their ability to accurately capture the views of decision-makers(DMs)in certain circumstances,such as when the DM hesitates between multiple linguistic terms or the decision information is incomplete,thus affecting their role in the decision-making process.Belief function theory is a leading streamof thought in uncertainty processing that is suitable for dealing with the limitations of PLTS.Therefore,the purpose of this study is to extend PLTS to incorporate belief function theory.First,we provide the basic concepts of the extended PLTS(i.e.,belief-based PLTS)through case analyses.Second,the aggregation operator of belief-based PLTS is defined with the ordered weighted average(OWA)-based soft likelihood function,which is improved by considering the reliability of the information source.Third,to measure the magnitude of different belief-based PLTSs,the belief interval of singleton is calculated,and the comparison method of belief-based PLTS is constructed based on probabilities.On the basis of the preceding discussion,we further develop an emergency decision framework that includes several novel techniques,such as attribute weight determination and decision information aggregation.Finally,the usefulness of the framework is demonstrated through a case study,and its effectiveness is illustrated through a series of comparisons.

A Novel Multi-Attribute Decision-Making Method Based on Probabilistic Hesitant Fuzzy Soft Set and Its Application

The probabilistic hesitant fuzzy multi-attribute group decision-making method introduces probability and hesitation into decision-making problems at the same time,which can improve the reliability and accuracy of decision-making results,and has become a research hotspots in recent years.However,there are still many problems,such as overly complex calculations and difficulty in obtaining probability data.Based on these,the paper proposes a multi-attribute group decision-making model based on probability hesitant fuzzy soft sets.Firstly,the definition of probabilistic hesitant fuzzy soft set is given.Then,based on soft set theory and probabilistic hesitant fuzzy set,the similarity measure of probabilistic hesitant fuzzy soft set is proposed,and the two measures are further combined.Finally,it is applied to the construction of multi-attribute group decision-making model,and the effectiveness and rationality of the model are verified by an example.The example shows that the new similarity calculation formula and algorithm model in this paper have higher accuracy,and the calculation process is more simple,it provides a feasible method for multi-attribute group decision making problems.

Multi-Attribute Preferences Mining Method for Group Users with the Process of Noise Reduction

Traditional researches on user preferences mining mainly explore the user’s overall preferences on the project,but ignore that the fundamental motivation of user preferences comes from their attitudes on some attributes of the project.In addition,traditional researches seldom consider the typical preferences combination of group users,which may have influence on the personalized service for group users.To solve this problem,a method with noise reduction for group user preferences mining is proposed,which focuses on mining the multi-attribute preference tendency of group users.Firstly,both the availability of data and the noise interference on preferences mining are considered in the algorithm design.In the process of generating group user preferences,a new path is used to generate preference keywords so as to reduce the noise interference.Secondly,the Gibbs sampling algorithm is used to estimate the parameters of the model.Finally,using the user comment data of several online shopping websites as experimental objects,the method is used to mine the multi-attribute preferences of different groups.The proposed method is compared with other methods from three aspects of predictive ability,preference mining ability and preference topic similarity.Experimental results show that the method is significantly better thap other existing methods.

A Confidence-based Consensus Model for Multi-Attribute Group Decision Making:Exploring the Bounded Trust Propagation and Personalized Adjustment Willingness

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.To address these problems,this paper explores a confidence-based MCC model that considers DMs’adjustment willingness in the STN.The proposed model includes several modifications to the traditional trust propagation and consensus optimization models.Firstly,the improved method for measuring CLs of DMs and the confidence-based normalization approach are defined,respectively.Secondly,the bounded trust propagation operator is proposed,which considers the credibility of mediators to complete the STN.Thirdly,the identification rules based on the consensus index and CL are defined,and the MCC model with personalized cost functions and acceptable adjustment thresholds is built to automatically generate adjustment values for non-consensus DMs.Finally,a model to identify the non-cooperative behavior at the element level is established and the hybrid MCC model with persuasion strategies is provided.Finally,a case study is processed to verify the applicability of the proposed model,and comparison and sensitivity analysis are conducted to highlight its benefits.

基于直觉模糊VIKOR方法的装备优选群决策模型

针对属性权重完全未知且属性值为语言信息的装备优选与排序问题,提出了一种基于扩展多准则妥协解排序(VIKOR)的多属性群决策模型。该模型引入直觉模糊加权集结(IFWA)算子对所有个体的决策信息进行集成,以获取作战指挥员决策群组的直觉模糊决策矩阵。利用直觉模糊数熵权公式对评估属性进行客观赋权,通过将VIKOR法扩展到直觉模糊环境来得到待选装备的折衷可行方案。最后结合作战无人机(UCAV)空地导弹优选实例和灵敏度分析验证了该模型的有效性和稳定性,并通过与直觉模糊TOPSIS法的对比实验表明了所提出方法的优越性。

发电集团竞价决策及支持系统模式探讨

厂网分开、竞价上网是我国目前电力市场改革的一个重要特征,市场模式下各发电企业的竞价结果直接决定其经营收益。与单一电厂相比,在一个市场中拥有多个电厂的发电集团能够掌握更多的市场信息。为减少内部竞争,为实现集团整体利益最大化经营目标,有必要对各下属电厂的生产经营进行管理和指导,引导所属电厂积极主动的参与市场竞争。针对发电集团参与电力市场的需求,该文提出了分散部署、分散决策,集中部署、分散决策和集中部署、集中决策三种典型的发电集团竞争决策模式;分析了每种决策模式的特点和相应电力市场管理系统的建设方式;分析表明,随着电力市场的不断发展和成熟,发电集团的竞价决策模式将逐步由分散部署、分散决策过渡到集中部署、分散决策,最终实现集中部署、集中决策。

团队思维及领导者在其形成过程中的引领力研究

经济社会的愈加复杂决定了决策的愈加困难,团队思维是避免非理性决策行为,提高群体决策质量的必然要求,本文从群体决策过程中的常见非理性行为入手,提出了团体思维的定义,分析了其形成的机理,并对其形成过程中的最重要因素领导者的引领力进行了深入探讨。

基于有限理性的投资项目评价与决策研究

现行的项目经济评价方法的隐含假设,是古典经济学的"完全理性"。但现实中的人做不到完全理性。西蒙从心理学角度提出了"有限理性"假说。项目评价与决策的有限理性有多种表现。决策的三要素———目标、方案、决策行为,都很大程度地受到有限理性的影响,并会导致一定的决策效果偏差。有限理性对于不同类型项目的影响方式又有着重要的差异。为应对有限理性的消极影响,应对决策活动进行一些规制:首先,调整决策预期和决策行为,既然最优选择可遇不可求,能够获得满意方案即可;其次,在决策方式上,灵活地采取诸如群体决策、集中/分散决策、柔性决策等方式,来尽量消除有限理性的影响。

Relative Efficiency Evaluation on Water Resource Utilization

Water resource allocation was defined as an input-output question in this paper, and a preliminary input-output index system was set up. Then GEM （group eigenvalue method）-MAUE （multi-attribute utility theory） model was applied to evaluate relative efficiency of water resource allocation plans. This model determined weights of indicators by GEM, and assessed the allocation schemes by MAUE. Compared with DEA （Data Envelopment Analysis） or ANN （Artificial Neural Networks）, the mode was more applicable in some cases where decision-makers had preference for certain indicators

Fuzzy distances based FMAGDM compromise ratio method and application

An extended compromise ratio method（CRM） based on fuzzy distances is developed to solve fuzzy multi-attribute group decision making problems in which weights of attributes and ratings of alternatives on attributes are expressed with values of linguistic variables parameterized using triangular fuzzy numbers.A compromise solution is determined by introducing the ranking index based on the concept that the chosen alternative should be as close as possible to the positive ideal solution and as far away from the negative ideal solution as possible simultaneously.This proposed method is compared with other existing methods to show its feasibility and effectiveness and illustrated with an example of the military route selection problem as one of the possible applications.

基于CL-TOPSIS法的我国高技术企业技术创新能力评价研究

基于高技术企业技术创新能力综合指标体系构建分析,针对传统TOPSIS模型运用概念格加权群决策方法进行有效改进,试图通过实证分析深入剖析和系统识别高技术企业技术创新能力的关键影响因素,旨在为高技术企业技术创新能力内在因素相关研究在方法论层面提供有益借鉴,对未来更深入的研究奠定理论基础和准备。

Generalized dominance-based rough set approach to security evaluation with imprecise information

The model of grey multi-attribute group decision-making （MAGDM） is studied, in which the attribute values are grey numbers. Based on the generalized dominance-based rough set approach （G-DR- SA）, a synthetic security evaluation method is presented. With-the grey MAGDM security evaluation model as its foundation, the extension of technique for order performance by similarity to ideal solution （TOPSIS） integrates the evaluation of each decision-maker （DM） into a group＇s consensus and obtains the expected evaluation results of information system. Via the quality of sorting （QoS） of G-DRSA, the inherent information hidden in data is uncovered, and the security attribute weight and DMs＇ weight are rationally obtained. Taking the computer networks in a certain university as objects, the example illustrates that this method can effectively remove the bottleneck of the grey MAGDM model and has practical significance in the synthetic security evaluation.

Synthetic security assessment based on variable consistency dominance-based rough set approach

Security assessment can help understand the security conditions of an information system and yield results highly conducive to the solution of security problems in it. Taking the computer networks in a certain university as samples, this paper, with the information system security assessment model as its foundation, proposes a multi-attribute group decision-making （MAGDM） security assessment method based on a variable consistency dominance-based rough set approach （VC-DRSA）. This assessment method combines VC-DRSA with the analytic hierarchy process （AHP）, uncovers the inherent information hidden in data via the quality of sorting （QoS）, and makes a synthetic security assessment of the information system after determining the security attribute weight. The sample findings show that this method can effectively remove the bottleneck of MAGDM, thus assuming practical significance in information system security assessment.

Pythagorean probabilistic hesitant triangular fuzzy aggregation operators with applications in multiple attribute decision making

As a generalization of fuzzy set,hesitant probabilistic fuzzy set and pythagorean triangular fuzzy set have their own unique advantages in describing decision information.As modern socioeconomic decision-making problems are becoming more and more complex,it also becomes more and more difficult to appropriately depict decision makers’cognitive information in decision-making process.In order to describe the decision information more comprehensively,we define a pythagorean probabilistic hesitant triangular fuzzy set(PPHTFS)by combining the pythagorean triangular fuzzy set and the probabilistic hesitant fuzzy set.Firstly,the basic operation and scoring function of the pythagorean probabilistic hesitant triangular fuzzy element(PPHTFE)are proposed,and the comparison rule of two PPHTFEs is given.Then,some pythagorean probabilistic hesitant triangular fuzzy aggregation operators are developed,and their properties are also studied.Finally,a multi-attribute decision-making(MADM)model is constructed based on the proposed operators under the pythagorean probabilistic hesitant triangular fuzzy information,and an illustration example is given to demonstrate the practicability and validity of the proposed decision-making method.