基于粗糙集和灰色的供应链知识共享风险预警

从分析供应链的重要组织形式—虚拟企业的知识共享风险预警的评价标准入手,提出具有层次结构的风险预警评价属性模型。然后,利用粗糙集和灰色的基本理论和方法,建立基于粗糙集和灰色理论的供应链知识共享风险预警模型框架结构图,并给出其中的基于分辨矩阵的指标属性约简算法,优化评价指标。在此基础上,使用灰色理论对知识共享的风险进行评估。最后通过实例说明该预警模型的有效性及实用性。     

基于粗集和模糊集物流联盟知识共享风险预警

基于对有关物流联盟（虚拟物流）知识共享文献的综述,提出物流联盟知识共享风险预警评价指标体系。然后,利用粗糙集和模糊集的基本理论和方法,建立物流联盟知识共享风险预警模型,并给出基于分辨矩阵的指标属性约简算法,优化模型的评价指标。在此基础上,使用模糊集理论对物流联盟知识共享的风险进行评估。最后通过实例说明该预警模型的有效性及实用性。     

水产品安全评价指标约简方法研究

影响食品安全评价的因素很多,并且这些因素错综复杂,因此,目前众多算法存在评价指标约简效果差、运算效率低下等问题。针对大多数食品安全评价指标约简算法时间复杂度比较高、指标选取差等问题,文中利用粗糙集理论提出了一种新的解决办法。该方法基于相似矩阵概念,利用属性在相似矩阵中出现的频率给出了属性重要性的计算公式,以此作为启发式知识来约简决策表中的冗余属性,并将折半查询的思想运用到了算法中,加快了约简效率,提高了评价指标选取水平。实验结果表明该算法是简单有效的。     

概念格属性约简的启发式算法

概念格是知识处理与分析的一个有力的工具,在知识约简和数据挖掘方面有着重要的应用。该文首先从概念外延的角度研究了合理刻画属性重要性的指标,并给出了概念格属性约简的判定定理,然后以这些指标作为启发式信息设计了一种新颖的概念格启发式属性约简算法,最后通过实例表明了该约简算法的可行性与有效性。     

基于依赖度的区间集决策信息表属性约简

区间集决策信息表拓展了经典决策信息表,但其属性约简研究较少.针对区间集决策信息表存在的问题,采用模型正域及相关依赖度提出属性约简及其启发式约简算法.在区间集粗糙集模型中,定义关于决策分类的正域与依赖度,证明粒化单调性等性质.提出基于依赖度的属性约简,设计启发式约简算法.实例分析与数据实验表明,设计的基于依赖度的启发式约简算法是有效的,所得结果有利于依赖学习与特征优化.     

基于概念格外延信息量的属性约简算法

概念格是知识处理与分析的一个有力的工具,在知识约简和数据挖掘方面有着重要的利用。首先给出了概念格外延信息量的概念,在此基础上研究了合理刻画属性重要性的指标,并给出了概念格核心属性的判定定理,然后以这些指标作为启发式信息设计了一种新颖的概念格启发式属性约简算法,最后通过实例表明了该约简算法的可行性与有效性。     

基于模糊多属性决策的虚拟企业风险评价方法

虚拟企业在帮助企业获得反应灵活性的同时,也不可避免地蕴涵了诸多风险因素。在分析虚拟企业风险评价应该考虑的主要因素的基础上,建立了一套适用于虚拟企业风险评价的指标体系。并以三角模糊数的形式给出指标值和评价者的主观感觉值,将基于期望值的模糊多属性决策法引入虚拟企业的风险评价中。同时讨论了指标权重完全未知和部分未知时虚拟企业的风险评价问题,得到虚拟企业方案综合选择的优先顺序。实例说明了虚拟企业风险评价的具体过程。     

一种基于知识粒度的不完备信息系统的属性约简算法

在不完备信息系统中，通过引入知识粒度的概念，对属性的重要性进行了定义，并以属性重要性为启发式信息，提出一种基于知识粒度的属性约简启发式算法，该算法的时间复杂度是多项式的，最后通过例子说明，该算法能得到不完备信息系统的一个约简。     

基于可辨识矩阵的启发式属性约简方法及其应用

在基于可辨识矩阵的属性约简算法的基础上，提出了基于可辨识矩阵的计算属性重要性的方法，并以此作为启发式知识来约简决策表中的冗余属性。这种方法直接源于评审数据，思路清晰，拟合结果表明本约简算法合理、可靠。     

基于属性排斥矩阵的约简方法

针对启发式算法难以获得最小约简的问题,研究最小约简约束下属性之间的排斥特性,提出了针对部分最小约简必要条件的属性排斥矩阵.在此基础上,分别结合典型加法类和减法类启发式约简算法提出两种改进的基于属性排斥矩阵的启发式属性约简算法,采用UCI(加州大学欧义分校)机器学习数据集所进行的测试结果表明,属性排斥矩阵能够全面提高启发式属性约简算法的性能,有利于获得最小约简.     

A fuzzy trust evaluation method for knowledge sharing in virtual enterprises

The success of virtual enterprises (VEs) depends on the effective sharing of related resources between various enterprises or workers who perform related activities. Specifically, VE success hinges on the integration and sharing of information and knowledge. Trust is an important facilitator of knowledge sharing. However, the trustworthiness of a peer is a vague concept that is dynamic and that often shifts over time or with environmental changes. This study designs a trust-based knowledge-sharing model based on characteristics of VEs and the knowledge structure model to express knowledge associated with VE activities. Subsequently, the factors that affect the trust evaluation are identified based on the characteristics of trust and VEs. Finally, this study develops a knowledge sharing, decision-making framework in which a fuzzy trust evaluation method for sharing knowledge is proposed based on VE activities and the interactions among workers in allied enterprises. The method consists of three sub-methods, including an activity correlation evaluation method, a current trust evaluation method, and an integral trust evaluation method. Under the premises of secure VE knowledge and reasonable access authorization, the proposed knowledge-sharing method provides the trust level between a knowledge-requesting enterprise and a knowledge-supplying enterprise to improve the willingness of the latter to share more valuable knowledge, ultimately increasing the efficiency and competitiveness of VEs.     

A fuzzy trust evaluation method for knowledge sharing in virtual enterprises

The success of virtual enterprises (VEs) depends on the effective sharing of related resources between various enterprises or workers who perform related activities. Specifically, VE success hinges on the integration and sharing of information and knowledge. Trust is an important facilitator of knowledge sharing. However, the trustworthiness of a peer is a vague concept that is dynamic and that often shifts over time or with environmental changes. This study designs a trust-based knowledge-sharing model based on characteristics of VEs and the knowledge structure model to express knowledge associated with VE activities. Subsequently, the factors that affect the trust evaluation are identified based on the characteristics of trust and VEs. Finally, this study develops a knowledge sharing, decision-making framework in which a fuzzy trust evaluation method for sharing knowledge is proposed based on VE activities and the interactions among workers in allied enterprises. The method consists of three sub-methods, including an activity correlation evaluation method, a current trust evaluation method, and an integral trust evaluation method. Under the premises of secure VE knowledge and reasonable access authorization, the proposed knowledge-sharing method provides the trust level between a knowledge-requesting enterprise and a knowledge-supplying enterprise to improve the willingness of the latter to share more valuable knowledge, ultimately increasing the efficiency and competitiveness of VEs.     

基于模糊邻域粗糙集的启发式属性约简算法

属性约简是机器学习等领域中常用的数据预处理方法。在基于粗糙集理论的属性约简算法中,大多是根据单一的方法来度量属性重要度。为了从多角度对属性达到更为优越的评估效果,首先在已有的模糊邻域粗糙集模型中定义属性依赖度度量,然后根据粒计算理论中知识粒度的概念,在模糊邻域粗糙集模型下提出了模糊邻域粒度度量。由于属性依赖度和知识粒度代表了不同视角的属性评估方法,因此将这两种方法结合起来用于信息系统的属性重要度评估,最后给出一种启发式属性约简算法。实验结果表明,所提出的算法具有较好的属性约简性能。     

Knowledge sharing in dynamic virtual enterprises: A socio-technological perspective

The success of a virtual enterprise depends largely on the effective collaboration of its members in orchestrating their knowledge, skills, core competences and resources, in order to enhance competitive capabilities and respond better to business opportunities. In this paper we address the challenges of knowledge sharing in dynamic virtual enterprises. We take a socio-technological approach by proposing a human-centered knowledge sharing solution and architecture. Specifically, we propose a knowledge resource space model to represent heterogeneous knowledge resources, both explicit and implicit. We then introduce a knowledge sharing community model and adopt an agent based solution to perform the functions of knowledge sharing among members of a dynamic virtual enterprise. Our solution incorporates the concepts of agent society and semantic ontology. Knowledge sharing in dynamic virtual enterprises is performed with three types of ties: knowledge agent to knowledge agent, knowledge agent to knowledge item, and knowledge item to knowledge item. We measure agent-to-agent ties by preference correlation using the contribution degree of one agent to another and the preference similarity degree between two agents. We define a semantic view to show agent-to-item ties and use semantic links in the knowledge resource space model to reflect item-to-item ties. We also elaborate the co-evolution mechanism of collective intelligence across enterprises throughout the lifecycle of a dynamic virtual enterprise. A case study is presented to validate our approach.     

Secure resource sharing on cross-organization collaboration using a novel trust method

A virtual enterprise (VE) consists of a network of independent, geographically dispersed administrative business domains that collaborate with each other by sharing business processes and resources across enterprises to provide a value-added service to customers. Therefore, the success of a VE relies on full information transparency and appropriate resource sharing, making security and trust among subjects significant issues. Trust evaluation to ensure information security is most complicated in a VE involving cross-organization collaboration. This study presents a virtual enterprise access control (VEAC) model to enable resource sharing for collaborative operations in the VE. A scenario for authentication and authorization in the life cycle of a VE is then described to identify the main activities for controlling access. Also developed herein is a trust evaluation method based on the VEAC model to improve its security while safeguarding sensitive resources to support collaborative activities. The trust evaluation method involves two trust evaluation sub-models, one to evaluate the level of trust between two virtual enterprise roles, and another to measure the level of trust between two projects. The two sub-models support each other to make resource-sharing decisions, and are developed based on the concepts of direct, indirect, and negative trust factors. Finally, an example of measuring the trust between two subjects is demonstrated after introducing the two sub-models. The VEAC-based trust evaluation method enables the following: (1) secure resource sharing across projects and enterprises, (2) collaborative operation among participating workers, (3) increased information transparency and (4) lowered information delay in VEs.     

基于BP神经网络的虚拟企业风险评价研究

虚拟企业是21世纪企业的潜在发展模式,虚拟企业在帮助企业获得反应灵活性的同时,也不可避免地蕴涵了诸多的风险因素.在研究阐述风险管理理论的基础上.全面考察影响虚拟企业整体风险水平的各种因素,针对目前风险研究不足的现状,根据虚拟企业的特点,构造了虚拟企业风险评价指标体系,提出了一种基于BP神经网络的虚拟企业风险评判方法,通过MATLAB神经网络工具对其进行仿真计算,并给出了一个实例来验证模型的可靠性,实例研究表明该方法为虚拟企业风险评价提供了一种有效的管理工具.     

基于粗糙集和灰色理论的物流联盟稳定性研究

基于对有关战略联盟稳定性文献的综述,提出具有层次结构的物流联盟稳定性评价属性模型。然后,利用粗糙集和灰色的基本理论和方法,建立基于粗糙集和灰色理论的物流联盟稳定性状况评价模型框架结构图,并给出其中的基于分辨矩阵的指标属性约简算法,优化评价指标。在此基础上,使用灰色理论对物流联盟的稳定性状况进行评估。最后通过实例说明该模型的有效性及实用性。