DocumentCode
2881481
Title
A neural network application for bankruptcy prediction
Author
Raghupathi, Wullianallur ; Schkade, Lawrence L. ; Raju, Bapi S.
Author_Institution
Texas Univ., Arlington, TX, USA
Volume
iv
fYear
1991
fDate
8-11 Jan 1991
Firstpage
147
Abstract
Discusses an application of the back error propagation network for making bankruptcy prediction decisions. Results of simulations with one and two hidden layers with varying nodes are presented. It is observed that the configuration with two hidden layers had a superior classification accuracy compared to the one with a single hidden layer. Based on the initial results it appears that neural network algorithms can be investigated further as potential models for bankruptcy prediction
Keywords
classification; financial data processing; neural nets; back error propagation network; bankruptcy prediction; classification accuracy; hidden layers; neural network; simulations; varying nodes; Decision support systems; Guidelines; Industrial relations; Investments; Neural networks; Performance analysis; Portfolios; Predictive models; Synthetic aperture sonar; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
System Sciences, 1991. Proceedings of the Twenty-Fourth Annual Hawaii International Conference on
Conference_Location
Kauai, HI
Type
conf
DOI
10.1109/HICSS.1991.184054
Filename
184054
Link To Document