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Enterprise credit risk evaluation based on neural network algorithm - 2018

Research Area:  Machine Learning

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.

Author(s) Name:  Xiaobing Huang,Xiaolian and Liu Yuanqian Ren

Journal name:  Cognitive Systems Research

Conferrence name:  

Publisher name:  ELSEVIER

DOI:  10.1016/j.cogsys.2018.07.023

Volume Information:  Volume 52, December 2018, Pages 317-324