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针对中小企业信用风险的非系统性、外部环境高依赖性等特性,本文建立了基于元胞蚂蚁算法的信贷风险跟踪预警监测模型。该模型先利用蚂蚁算法寻优特性,将样本企业有效聚类并将测试企业归类,再利用元胞演变机制反应其潜在风险因素,进而对风险进行预警。实证检验证明,该算法在对企业聚类、分类和风险预警方面均有较好的表现,优越性明显。
In view of the non-systematic credit risk of SMEs and the high dependency of external environment, this paper establishes a credit risk tracking and early warning monitoring model based on cellular ant algorithm. The model first uses the ant algorithm to optimize the characteristics of the sample business clustering effectively and test the business classification, and then use cellular evolution mechanism to reflect its potential risk factors, and then risk warning. The empirical test proves that the algorithm has good performance in the aspects of enterprise clustering, classification and risk warning, and the superiority is obvious.