A Comparative Analysis of Artificial Neural Networks Using Financial Distress Prediction
Article first published online: 25 MAR 2014
© 1994 John Wiley & Sons, Ltd.
Intelligent Systems in Accounting, Finance and Management
Volume 3, Issue 4, pages 241–252, December 1994
How to Cite
Fanning, K. M. and Cogger, K. O. (1994), A Comparative Analysis of Artificial Neural Networks Using Financial Distress Prediction. Int. J. Intell. Syst. Acc. Fin. Mgmt., 3: 241–252. doi: 10.1002/j.1099-1174.1994.tb00068.x
- Issue published online: 25 MAR 2014
- Article first published online: 25 MAR 2014
- Manuscript Revised: OCT 1994
- Manuscript Received: FEB 1993
This paper examines the efficiency of a generalized adaptive neural network algorithm (GANNA) processor in comparison to earlier model-based methods, a back-propagation artificial neural network, and logistic regression approaches to data classification. The research uses the binary classification problem of discriminating between failing and non-failing firms to compare the methods. The results indicate the potential in time savings and the successful classification results available from a GANNA processor.