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Grey Incidence Theory based Credit Discriminent In the Transaction of Power Energy

机译:基于灰色的发病理论基于信贷判别在权力交易中

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After restructured the electricity industry, trading among those utilities like generation plants, grid companies, retail agents becomes more and more frequently and complicatedly, and risk existed unavoidably. Credit Evaluation on the opponent is an effective measure to decreasing the potential losses. Firstly, different transaction mode in electricity market was analyzed, with the theory of credit, the credit management indices used in long-term contract transaction was constructed, which is of simpleness and practicality and is suitable for applying it into the primary electricity market. When credit evaluation is carried out, more or less, the information is uncertain; therefore, the grey incidence approach was employed. With the sample data given, which would imply their correlativity among those indices, we could use cluster grey incidence degree to determine the weight of every index automatically, and we also could compare the grey incidence degree of unknown object to that of the typical samples, then we would realize the credit rating that those new clients would be attributed to in advance, finally, a case verify the validity of the approach we presented.
机译:在重组电力行业后,在生成植物,电网公司,零售代理等公用事业中交易变得越来越复杂,并且不可避免地存在风险。对对手的信用评估是减少潜在损失的有效措施。首先,分析了电力市场中的不同交易模式,通过信贷理论,建设了长期合同交易中使用的信用管理指标,这是一种简单性和实用性,适用于将其施加到主要电力市场中。当进行信用评估时,或多或少地,信息不确定;因此,采用了灰色发生率接近。通过给出的示例数据,这将暗示它们在这些指标之间的相关性,我们可以使用群集灰色入射度来自动确定每个指数的重量,我们也可以将未知物体的灰色入射程度与典型样本的灰色入射程度进行比较,然后,我们将实现信用评级,即这些新客户将提前归因于,最后,案例验证了我们所提出的方法的有效性。

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