The study of small enterprises credit evaluation based on incremental AntClust

被引：0
|
作者：
Liang Xue-chun [1 ]
Chen Sen-fa [1 ]
Liu Yan [2 ]
机构：
[1] Southeast Univ, Econ Management Inst, Nanjing 210096, Peoples R China
[2] Nanjing Univ Technol, Syst Engn Res Inst, Nanjing 210009, Peoples R China
来源：
PROCEEDINGS OF 2007 IEEE INTERNATIONAL CONFERENCE ON GREY SYSTEMS AND INTELLIGENT SERVICES, VOLS 1 AND 2 | 2007年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The lending rate and lending credit rely on the accurate evaluation of the credit risk of small business. In this paper, according to the running processes in some commercial bank in Nanjing in China, we construct an index system for small business credit evaluation which is a combination of qualitative indices and quantitative ones. Moreover we present an incremental clustering algorithm based on the chemical recognition system of ants to produce index weights. At last we adopt empirical study and the result shows that the credit value of the business gained from the model is credible and accurate.
引用
收藏
页码：294 / 298
页数：5
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