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Building a Hybrid Method for Analyzing the Risk by Integrating the Fuzzy Logic and the Improved Fuzzy Clustering Algorithm FCM-R

机译:通过集成模糊逻辑和改进的模糊聚类算法FCM-R构建用于分析风险的混合方法

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Analysis of risk is a problem has attracted a special deal of consideration from enterprises. This paper proposes the integrating the fuzzy logic and the improved fuzzy clustering algorithm FCM-R to build a hybrid method for analyzing the risk. The method has two stages. In stage 1, first, the fuzzy logic is used to determine the risk levels of objects. The next, the objects which have risk level is greater or equal a given threshold, are selected for analyzing in the next stage. In stage 2, the improved fuzzy clustering algorithm FCM-R is applied to the objects chosen to create the appropriate number of clusters which are ranked based on the risk level measure of clusters. Here, for illustrating, we choose objects to analyze risk are customers in the enterprise. The proposed method has been experimented with real data set to generate customer clusters ranked according to the risk level measure from high to low. The results will be to use for predicting the customer's risk and will be to help for offering the risk management policies to avoid loss.
机译:风险分析是一个问题引起了企业的特殊考虑。本文提出了集成模糊逻辑和改进的模糊聚类算法FCM-R构建混合方法,用于分析风险。该方法有两个阶段。在第1阶段,首先,模糊逻辑用于确定对象的风险级别。接下来,选择具有风险等级的对象更大或等于给定阈值,以便在下一阶段分析。在第2阶段,改进的模糊聚类算法FCM-R应用于选择以创建基于集群风险级别测量的适当数量的簇的对象。在这里,为了说明,我们选择要分析风险的对象是企业中的客户。该方法已经尝试了真实数据集,以产生根据风险级别从高到低的风险级别测量排名的客户集群。结果将用于预测客户的风险,并有助于提供风险管理政策以避免损失。

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