基于启发式约简的虚拟企业知识共享风险预警

从虚拟企业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,利用粗糙集的基本理论和方法,建立基于启发式属性约简的虚拟企业知识共享风险预警模型框架结构图,并给出基于分辨矩阵的启发式指标属性约简算法,进行指标优化。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。     

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。     

知识共享效率的R-RNN评价模型研究及应用

针对企业知识共享效率评价方法缺乏的现状,提出了基于粗糙集和RBF神经网络的R-RNN知识共享效率评价模型。在研究知识共享活动基本过程的基础上,分析了知识共享效率影响因素,得出效率评价指标体系。然后,运用粗糙集理论对评价指标进行预处理,去除冗余指标项,在合理化评价指标体系的同时减少网络输入维度,进而采用RBF神经网络对知识共享效率进行综合评价。最后通过具体的应用实例验证了该评价模型的有效性与可行性。     

一种供应链绩效评价新方法及其应用

利用平衡记分法建立供应链绩效评价指标体系,利用粗糙集理论对绩效评价体系进行约简,得到约简后的指标集后,使用基于信息熵的多属性评价方法对供应链绩效进行评价和排序,以便决策者参考。经过实证分析,证明该方法是有效的供应链绩效评价方法。     

一种有效的供应链绩效预测方法及其应用

从知识发现和数据挖掘的角度,利用粗糙集和支持向量回归机的理论和方法,建立了基于粗糙集和支持向量回归机相结合的供应链绩效预测模型。结合一个供应链绩效预测实例,首先对其基于平衡记分卡的指标体系进行了约简,然后将约简的评价指标输入到支持向量回归机中进行训练,构建预测模型,最后把预测的样本输入到模型中进行供应链绩效预测,预测结果与实际结果基本吻合。     

虚拟企业伙伴选择的粗糙集方法

将粗糙集理论应用于虚拟企业合作伙伴选择中,提出了基于粗糙集理论的虚拟企业伙伴选择的模型和方法.该方法根据各潜在伙伴企业的样本数据集建立决策系统,以伙伴选择的评价指标作为属性,从中挖掘出反映评价指标本质关系的重要属性以及伙伴选择知识规则.这些规则很好地描述了有限样本中所反映出的属性之间的本质特征,运用这些规则可对伙伴选择数据库中的其他样本有效地进行伙伴选择.应用实例表明,该方法是正确有效的.     

基于粗糙集的供应链绩效改进决策研究

从知识发现和数据挖掘的角度,利用粗糙集的理论和方法,建立了基于粗糙集的供应链绩效改进决策模型框架,并给出其中的指标约简方法和基于分辨矩阵计算指标权重的数学模型。最后结合一个制造业供应链绩效评价实例,首先对其基于平衡记分卡的指标体系进行了约简,然后建立了基于粗糙集的供应链绩效改进决策模型,确定了指标的客观权重。并对结果进行了分析,提出了绩效改进决策意见和措施。     

双精度容差关系决策粗糙集及其属性约简

决策粗糙集理论是经典粗糙集理论结合贝叶斯理论拓展而来。为在不完备区间值信息系统下研究决策粗糙集理论,本文首先提出属性相似度的概念,并基于属性相似度定义了双精度容差关系。然后,基于双精度容差关系,结合贝叶斯最小风险决策原则建立不完备区间值信息系统下决策粗糙集模型。针对该模型,对不确定性度量进行修正并基于修正的不确定性度量对该模型的属性约简进行研究。最后提出属性约简算法并应用于目标识别实例。     

基于粗糙集和神经网络的供应链绩效预测研究

文章从知识发现和数据挖掘的角度,利用粗糙集和BP神经网络的理论和方法,建立了基于粗糙集和BP神经网络相结合的供应链绩效预测模型。并结合一个供应链绩效预测实例,首先对其基于平衡记分卡的指标体系进行了约简,然后将约简的评价指标输入到BP神经网络中进行智能训练,最后把预测的样本输入到训练好的BP网络中得出供应链绩效的预测值,预测结果与实际结果基本吻合。     

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。     

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.     

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。