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Enterprise Credit Guarantee Program Risk Assessment: Based on BP-ANN Evaluation Model

机译:企业信用担保计划风险评估:基于BP神经网络的评估模型

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We evaluated the projects risk by using the Back Propagation neural network model, then set up the risk evaluation indexes of enterprise credit guarantee projects. The training samples, verification samples and testing samples that the model needed were generated by the randomly get arms method in the range of single-index evaluation standard. The case study indicates that the methodology for generating samples and the process for establishing BP-ANN model are effective and reliable. The phenomenon of over-training and over fitting can be effectively escaped, the model possesses good generalization. Comparing to the methodology of Fuzzy theory, the influence by personal factors can be escaped.
机译:我们采用反向传播神经网络模型对项目风险进行了评估,然后建立了企业信用担保项目的风险评估指标。模型所需的训练样本,验证样本和测试样本是通过单指标评估标准范围内的随机获得臂方法生成的。案例研究表明,生成样本的方法和建立BP-ANN模型的过程是有效和可靠的。可以有效地避免过度训练和过度拟合的现象,该模型具有良好的推广性。与模糊理论的方法相比,可以避免个人因素的影响。

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