Credit rating analysis with support vector machines and artificial bee colony algorithm

Mu Yen Chen, Chia Chen Chen, Jia Yu Liu

研究成果: Conference contribution

6 引文 斯高帕斯(Scopus)

摘要

Recently, credit rating analysis for financial engineering has attracted many research attentions. In the previous, statistical and artificial intelligent methods for credit rating have been widely investigated. Most of them, they focus on the hybrid models by integrating many artificial intelligent methods have proven outstanding performances. This research proposes a newly hybrid evolution algorithm to integrate artificial bee colony (ABC) with the support vector machine (SVM) to predict the corporate credit rating problems. The experiment dataset are select from 2001 to 2008 of Compustat credit rating database in America. The empirical results show the ABC-SVM model has the highest classification accuracy. Hence, this research presents the ABC-SVM model could be better suited for predicting the credit rating.

原文English
主出版物標題Recent Trends in Applied Artificial Intelligence - 26th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2013, Proceedings
頁面528-534
頁數7
DOIs
出版狀態Published - 2013
事件26th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2013 - Amsterdam, Netherlands
持續時間: 2013 六月 172013 六月 21

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
7906 LNAI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference26th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2013
國家/地區Netherlands
城市Amsterdam
期間13-06-1713-06-21

All Science Journal Classification (ASJC) codes

  • 理論電腦科學
  • 電腦科學(全部)

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