The Study on Credit Rating Model of Listed Companies

机译：上市公司信用评级模型研究

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Minimizing the credit risk of banking business is of great importance in China today. This paper proposes a rating method based on the FSDB algorithm. In addition, an SOM Neural Network model for credit rating is proposed. Simulation tests show that after being trained by the given sample credit data of listed companies, the model can be used for credit rating with high veracity.

机译：在当今的中国，最大限度地降低银行业务的信用风险非常重要。提出了一种基于FSDB算法的评分方法。此外，提出了一种用于信用评级的SOM神经网络模型。仿真测试表明，该模型经过给定的上市公司信用数据样本训练后，可用于较高准确性的信用评级。

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来源
《Fifth Wuhan International Conference on E-Business: Integration and Innovation through Measurement and Management vol.2》|2006年|1679-1685|共7页
会议地点 Wuhan(CN)
作者
Dedong Zhang; Li Zhang; Qiang Zhang;
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作者单位

School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China;

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会议组织
原文格式 PDF
正文语种 eng
中图分类商业企业组织与管理;计算技术、计算机技术;
关键词
credit rating model; feature selecting; SOM neural network;

机译：信用评级模型；特征选择； SOM神经网络;

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The Study on Credit Rating Model of Listed Companies

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