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Information Processing in HFMFs Based Risk Evaluation for Virtual Enterprise

机译:基于HFMFS的虚拟企业风险评估信息处理

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The method of HFMFs (Hypertrapezoidal Fuzzy Membership Functions) is a new mechanism for designing multidimensional fuzzy sets. HFMFs models the correlation that exists between the variables of the state space. Therefore, it is able to describe the problems of fuzzy situation more exactly. As we known, it needs a great many information to evaluate the risk level for VE using fuzzy synthetic evaluation method. However, there are lots of difficulties to get the needed information for VE. Accordingly, the HFMFs method is introduced to estimate the risk level of VE. Considering not only the relations between different fuzzy sets but also the method of HFMFs is able to describe the problems of fuzzy situation more exactly with less information. Consequently, the HFMFs method is more suitable to the virtual enterprise with little historical experiences than the fuzzy synthetic evaluation method. Simulation has shown that this method is a simple and effective risk evaluation method for VE.
机译:HFMFS(Hypraptapoidal模糊隶属函数)的方法是设计多维模糊集的新机制。 HFMFS模拟状态空间变量之间存在的相关性。因此,它能够更确切地描述模糊情况的问题。众所周知,它需要使用模糊综合评估方法来评估VE的风险等级。但是,获得了许多困难来获得所需的信息。因此,引入了HFMFS方法以估计VE的风险等级。不仅考虑了不同模糊集之间的关系,而且,HFMF的方法也能够更少于信息描述模糊情况的问题。因此,HFMFS方法更适合于虚拟企业,其历史经验略高于模糊综合评价方法。模拟表明,该方法是VE的简单有效的风险评估方法。

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