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.

Information Aggregation of Group Decision-Making in Emergency Events

Information is a key factor in emergency management, which helps decision makers to make effective decisions. In this paper, aiming at clarifying the information aggregation laws, and according to the characteristic of emergency information, information relative entropy is applied in the information aggregation to establish the information aggregation model of emergency group decision-making. The analysis shows that support and credibility of decision rule are the two factors in information aggregation. The results of four emergency decision-making groups in case study support the analysis in the paper.

Group Decision-Making Model of Renal Cancer Surgery Options Using Entropy Fuzzy Element Aczel-Alsina Weighted Aggregation Operators under the Environment of Fuzzy Multi-Sets

Since existing selection methods of surgical treatment schemes of renal cancer patients mainly depend on physicians’clinical experience and judgments,the surgical treatment options of renal cancer patients lack their scientifical and reasonable information expression and group decision-making model for renal cancer patients.Fuzzy multi-sets(FMSs)have a number of properties,which make them suitable for expressing the uncertain information of medical diagnoses and treatments in group decision-making(GDM)problems.To choose the most appropriate surgical treatment scheme for a patient with localized renal cell carcinoma(RCC)(T1 stage kidney tumor),this article needs to develop an effective GDM model based on the fuzzy multivalued evaluation information of the renal cancer patients.First,we propose a conversionmethod of transforming FMSs into entropy fuzzy sets(EFSs)based on the mean and Shannon entropy of a fuzzy sequence in FMS to reasonably simplify the information expression and operations of FMSs and define the score function of an entropy fuzzy element(EFE)for ranking EFEs.Second,we present the Aczel-Alsina t-norm and t-conorm operations of EFEs and the EFE Aczel-Alsina weighted arithmetic averaging(EFEAAWAA)and EFE Aczel-Alsina weighted geometric averaging(EFEAAWGA)operators.Third,we develop a multicriteria GDM model of renal cancer surgery options in the setting of FMSs.Finally,the proposed GDM model is applied to two clinical cases of renal cancer patients to choose the best surgical treatment scheme for a renal cancer patient in the setting of FMSs.The selected results of two clinical cases verify the efficiency and rationality of the proposed GDM model in the setting of FMSs.

Shared Decision-Making after Implementation of the Chronic Care Model (CCM)—An Evaluative Approach

Background: In paternalistic models, healthcare providers’ responsibility is to decide what is best for patients. The main concern is that such models fail to respect patient autonomy and do not promote patient responsibility. Aim: To evaluate mental healthcare team members’ perceptions of their own role in encouraging elderly persons to participate in shared decision-making after implementation of the CCM. The CCM is not an explanatory theory, but an evidence-based guideline and synthesis of best available evidence. Methods: Data were collected from two teams that took part in a focus group interview, and the transcript was analysed by means of qualitative thematic analysis. Results: One overall theme emerged—Preventing the violation of human dignity based on three themes, namely, Changing understanding and attitudes, Increasing depressed elderly persons’ autonomy and Clarifying the mental healthcare team coordinator’s role and responsibility. The results of this study reveal that until recently, paternalism has been the dominant decision-making model within healthcare, without any apparent consideration of the patient perspective. Community mental healthcare can be improved by shared decision-making in which team members initiate a dialogue focusing on patient participation to prevent the violation of human dignity. However, in order to determine how best to empower the patient, team members need expert knowledge and intuition.

Group Decision-Making Method with Incomplete Intuitionistic Fuzzy Preference Relations Based on a Generalized Multiplicative Consistent Concept

Based on the analyses of existing preference group decision-making(PGDM)methods with intuitionistic fuzzy preference relations(IFPRs),we present a new PGDM framework with incomplete IFPRs.A generalized multiplicative consistent for IFPRs is defined,and a mathematical programming model is constructed to supplement the missing values in incomplete IFPRs.Moreover,in this study,another mathematical programming model is constructed to improve the consistency level of unacceptably multiplicative consistent IFPRs.For group decisionmaking(GDM)with incomplete IFPRs,three reliable sources influencing the weights of experts are identified.Subsequently,a method for determining the weights of experts is developed by simultaneously considering three reliable sources.Furthermore,a targeted consensus process(CPR)is developed in this study with reference to the actual situation of the consensus level of each IFPR.Meanwhile,in response to the proposed multiplicative consistency definition,a novel method for determining the optimal priority weights of alternatives is redefined.Lastly,based on the above theory,a novel GDM method with incomplete IFPRs is developed,and the comparative and sensitivity analysis results demonstrate the utility and superiority of this work.

重大突发事件下网络舆情传播中社会群体主题演化图谱构建研究

研究重大突发事件下网络舆情传播中社会群体主题演化图谱构建,对重大突发事件的应急和维护社会稳定具有重要作用。文章基于LDA主题模型构建社会群体主题演化图谱,基于主题时序统计和主题频次统计构建社会群体主题热度演化图谱,基于JS散度和DFS算法构建社会群体主题路径演化图谱,并给出重大突发事件下网络舆情传播中社会群体主题演化图谱构建过程模型。研究发现:利用构建的模型可以对群体主题特征、主题热度影响因素及主题最优传播路径进行分析,发现重大突发事件下舆情演进态势和识别敏感舆情话题,从而进行正向的舆情引导,为重大突发事件下网络舆情治理提供新的参考视角。

基于KANO模型的突发疫情事件社区弱势群体应急信息需求研究

[目的/意义]突发疫情事件中,社区是弱势群体获取应急信息的重要渠道,了解弱势群体信息需求,有助于社区精准提供信息服务,促进辖区内居民应急信息储备,增强其满意度。[方法/过程]文章以突发疫情为背景,结合疫情重要信息类别及相关文献,对社区内弱势群体应急信息需求展开调查,借助KANO问卷对各需求进行分类,以确定社区优化应急信息服务的优先级。[结果/结论]针对弱势群体的必备型需求、期望型需求、魅力型需求、无差异型需求调整应急信息服务重点,通过关注应急需求转化、拓宽信息传播渠道等措施,保障弱势群体应急信息需求得以满足。

划片区组长负责制能级对应分层管理模式在急诊护理管理中的应用价值

目的研究划片区组长负责制能级对应分层管理模式在急诊护理管理中的应用价值。方法选取我院41名急诊科护理人员为研究对象,其中2020年1月至2022年1月采用常规急诊护理管理(n=41,管理前),2022年2月至2023年1月采用划片区组长负责制能级对应分层管理模式(n=41,管理后)。选择同期我院急诊科收治的80例患者的临床资料开展回顾性分析,其中2020年1月至2022年1月纳入40例患者,2022年2月至2023年1月纳入40例患者。比较管理前、后的护理不良事件发生率、护理质量、护士人文素质及患者安全胜任力。结果管理后的护理不良事件总发生率为5.00%,低于管理前的20.00%(P<0.05)。管理后的病区管理、护士工作能力、护士形象、护理服务态度、健康教育评分及总分均高于管理前(P<0.05)。管理后的职业道德素质、文化素质、法律素质、审美素质、心理素质评分及总分高于管理前(P<0.05)。管理后的知识因素、系统因素、态度因素、技能因素评分及总分高于管理前(P<0.05)。结论划片区组长负责制能级对应分层管理模式在急诊护理管理中的应用价值显著,可降低护理不良事件发生率,提高护理质量,提升护理人员的人文素质,值得推广。

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.

A method for emergency response alternative decision-making under uncertainty

In this paper,an emergency decision-making method,based on case-based reasoning and cloud model,is proposed to solve the risk decision-making problem in emergency response.Casebased reasoning,by allowing the decision-maker to referring to past decisions,introduces a short-cut to formulate feasible emergency alternatives.Cloud model is used to evaluate and optimise the emergency response alternatives.To evaluate emergency response alternatives,the decision criterion must be determined according to the aim and characteristics of emergency rescue in disasters or accidents.Then,the weight cloud and evaluation cloud of the decision criterion are determined by the Delphi method combined with backward cloud generator,and the synthesised cloud of each alternative is calculated through arithmetic rules of cloud.Finally,a ranking of all response alternatives can be determined,and the best alternative is selected.Case study shows that the method makes the conversion between qualitative description and quantitative indication more effective.

改进的模糊DEMATEL模型在码头群协同应急风险因素分析中应用

多个码头间的协同应急风险一直是阻碍码头群发展的卡脖子问题之一。为此,将决策试验和评价实验室(Decision-making Trial and Evaluation Laboratory,DEMATEL)方法引入风险领域,并提出用于分析多属性码头群协同应急风险因素的模糊DEMATEL模型。通过计算因素间的相互影响关系,成功地识别出了“协同应急人员培训和知识更新”“应急人员协同能力”“码头群应急预案的完备性”以及“码头群协同应急演习”4个关键因素,进而便于码头群管理者精准和高效的管理。DEMATEL模型的识别方法和计算结果对港口群协同应急风险因素辨识同样具有重要参考价值。

网络舆情影响下考虑心理参照点变化的多阶段群决策方法

针对突发公共事件演化过程受网络舆情态势影响可能导致决策结果不同的问题,提出一种网络舆情影响下考虑决策者心理参照点变化的多阶段群决策方法。首先,采用隐马尔科夫模型预测不同情景下采用不同应急方案的舆情状态转移概率;其次,提出基于事态演化趋势的决策者心理参照点更新机制,引入决策者损益敏感度刻画不同决策者风险偏好的异质性;再次,使用熵权法对各指标进行赋权,利用累积前景理论计算各方案的综合前景价值;最后,通过算例分析说明所提方法的有效性。结果表明:该方法更贴近实际决策过程,网络舆情态势可通过影响决策者心理参照点进而改变决策结果,为突发公共事件决策问题提供了新思路。

航站楼出发厅小团体旅客应急疏散仿真研究

航站楼出发厅旅客通常以小团体的形式结伴出行,其疏散行为有别于单独旅客的疏散行为。分析小团体旅客的行为特征,从期望速度和小团体内部作用力对于社会力模型改进;针对疏散过程,建立多智能体技术的疏散仿真模型,以某航站楼出发厅为例,模拟不同比率不同区域小团体旅客疏散场景。结果显示,随着小团体旅客比率的增加,整体区域的疏散时间和平均绕行距离也在增加,休息区相较商业区旅客疏散时间更长。

淮河干流污染团应急处置水质水量联合调度

针对淮河干流污染团事件应急处置的需求,对污染团事件的水质水量联合调度措施进行研究。构建淮河干流中游段的水动力水质模型,分析加大蚌埠闸流量、加大引江济淮流量、两者同时加大、背景调度(无引江济淮工程)和常规调度(有引江济淮工程,但不加大流量)5种调度方式对淮河干流污染团的应急处置效果。结果表明:从污染团离开研究区域时间、峰值长度、峰值质量浓度等角度看,不同调度方式对污染团的处置效果有所不同;加大蚌埠闸流量、加大引江济淮流量和两者同时加大对污染团的处置效果均比背景调度和常规调度更优。研究结果可为淮河干流突发水污染事件应急处置提供参考。

突发事件应急救援人员的分组方法研究

针对突发事件应急救援人员分组问题,给出了一种基于优化模型的分组方法。在本文中,首先描述了突发事件的应急救援人员分组问题;然后依据救援人员特征表现评价信息,计算救援人员完成不同任务的综合表现评价值;进一步地,以完成各救援任务的"效果"最好为目标,考虑每个救援人员只能被分到一个组里且每组中的人员数量要满足救援任务的需要,构建了救援人员分组的多目标优化模型,并通过求解优化模型来得到应急救援人员的分组方案。最后,通过一个算例分析说明了本文提出方法的可行性和有效性。

考虑协同效应的突发事件救援人员分组方法

针对突发事件的应急救援人员分组问题,提出了一种考虑人员间协同效应的应急救援人员分组方法。首先,对突发事件应急救援人员分组问题进行了描述。然后,基于系统协同理论的思想,提出了救援小组的协同度模型,定量化的度量救援人员间的协同效应。进一步地,综合考虑救援人员的基础效能与协同效应,基于协同度模型给出了救援人员完成不同任务的实际效能的表达式。在此基础上,以最大化各救援小组的实际效能为目标,构建了突发事件应急救援人员分组的优化模型,并给出了将这一多目标0-1二次规划模型转换为单目标0-1线性规划模型的方法,进而可求解并确定救援人员的最优分组方案。最后,通过一个实例分析说明了本文所提出方法的可行性和有效性。

基于区间偏好信息的不确定性应急局部群决策模型

针对突发事件应急决策的复杂性特征,本文提出一种专家基于领域知识对应急方案集合进行局部评价的群决策模型。以区间数互反判断矩阵对属性进行偏好评价,采用线性规划求解权重区间,并利用集值统计序列得到属性权重向量的平均估计;在专家局部评价基础上,基于目标优化方法对方案群权重进行分配,并同时得到专家权重;通过集结个体局部偏好得到应急决策群组成员对备选方案偏好的一致性排序。最后,以地铁火灾事故为例模拟仿真应急疏散方案的群决策,对模型的实际运用说明了模型的可行性与有效性。

优化护理分组管理模式在急诊护理管理中的应用

目的探讨优化护理分组管理模式在急诊护理管理的应用效果。方法自2015年1月开始我院急诊科实施优化护理分组管理模式对急诊患者实施护理干预。比较优化护理分组管理模式实施前(2012年12月-2014年12月)和护理分组模式实施后(2015年1月-2016年1月)的护理质量满意情况、护理技术满意情况、护理整体素质的满意情况。比较优化护理分组模式实施前和实施后的总抢救时间、静脉通道建立时间及药物应用时间。结果优化护理分组管理模式实施后的护理质量满意情况、护理技术满意情况及护理整体素质满意率分别高于实施前,差异有统计学意义(P<0.05)。优化护理分组管理模式实施后的总抢救时间、静脉通道建立时间及药物应用时间分别低于实施后,差异有统计学意义(P<0.05)。结论优化护理分组管理模式能够提高急诊病例抢救时效性,提高急诊护理满意率,值得借鉴。

基于手机微信群通讯方式对基层急性心肌梗死救治模式的探讨

目的探讨利用手机微信群开展急性ST段抬高型心肌梗死(STEMI)患者24 h急救"绿色通道"救治模式的作用。方法 2014年建立江苏省江阴市STEMI救治微信群,将全市50家社区卫生服务中心及医院的近200名医师通过手机微信群建立相互联系,在遇有怀疑急性心肌梗死(AMI)患者时,第一时间上传相关资料至江阴市人民医院心内科AMI救治组,明确AMI诊断及再灌注方案,并记录患者就诊-球囊扩张时间、入门-球囊扩张时间、住院天数、住院期间患者生存状况、心功能等,并与之前(2013年)同期STEMI患者的救治情况及生存状况进行对比。结果 2014年江阴市医疗机构共收治发病在24 h之内的STEMI患者190例,行急诊经皮冠状动脉介入治疗(PCI)172例,急诊溶栓4例,其余14例因患者原因未行上述治疗;相比2013年,STEMI患者178例,行急诊PCI154例,急诊溶栓4例,其余20例因患者原因未行上述治疗。自2014年开通手机微信群和快速转诊系统后,患者就诊-球囊扩张时间由2013年的(128.6±33.9)min缩短至2014年的(102.3±21.4)min(P<0.01);入门-球囊扩张时间由2013年的(76.5±18.3)min缩短至2014年的(62.3±13.8)min(P<0.01);住院天数由2013年的(8.8±2.4)d缩短至2014年的(7.1±1.9)d(P=0.045);2013年住院期间发生心血管事件22例,2014年发生12例(P=0.045)。结论手机微信群可快速传递心电图、心肌损伤标志物等重要信息,有利于上级医院快速会诊及下级医院及时转诊,能有效缩短患者就诊-球囊扩张时间,改善患者预后,提高患者生存率。该方法为AMI患者的救治提供了一种新模式。

基于区间值模糊熵的网络舆情突发事件应急群决策模型

随着社交网络的广泛使用,网络舆情突发事件的爆发由单一性向多发性转变。文章特别针对同时爆发的多个网络舆情突发事件,构建了应急群决策模型。首先提取可有效衡量网络舆情突发事件危机程度的指标,再运用区间值模糊熵计算其合理权重,采用加权集结得到各事件的综合效果区间值,通过两两比较所得的可能优先度排序即可得到舆情最为严重的突发事件.算例分析结果验证了模型的合理性,提高了应急处理效率,能帮助应急部门更好地处理网络舆情危机,提高舆情导控能力。