دانلود رایگان مقاله انگلیسی ارزیابی ریسک اعتباری سرمایه گذاری بر اساس الگوریتم شبکه عصبی - الزویر 2018

Abstract:

To explore the enterprise credit risk evaluation, the application effect of several common neural network models in Chinese small and medium-sized enterprise data sets was compared and the optimal parameters for each model were determined. In addition, the classification accuracy and the applicability of the model were compared, and finally the common problem of optimization neural network algorithm based on population was solved: need to determine the dimensions in advance. The experimental results showed that the probabilistic neural network (PNN) had the minimum error rate and second types of errors, while the PNN model had the highest AUC value and was robust. To sum up, the algorithm makes some contributions to solve the financing problem of small and medium-sized enterprises in China.

5. Conclusion

On the basis of the Chinese private SMEs based on data set, we compare the classification accuracy and applicability of several common neural network models and thus propose some corresponding suggestions for the specific application of the credit risk assessment model. In addition, we prove the error rate of several common credit risk assessment models. The experimental results showed that the probabilistic neural network (PNN) had the minimum error rate and second type of errors, and the PNN model had the highest AUC value and was robust.

The purpose is to make some contribution to solve the problem of financing for small and medium-sized enterprises in China. However, because of a variety of factors involved in credit risk assessment, we need further exploration and research in this field. The complexity of credit risk assessment is also in urgent need of interdisciplinary practice of multidisciplinary technology and theory