| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10322412 | Expert Systems with Applications | 2012 | 7 Pages |
Abstract
⺠This paper analyzed the yearly financial data of manufacturing corporations collected by the KODIT. ⺠We developed a financial distress prediction model based on radial basis function SVM. ⺠We compare the classification accuracy performance between our RSVM and AI techniques. ⺠The experiments demonstrate that RSVM always outperforms other models in the performance of financial distress predicting. ⺠This enhancement in predictability of future financial distress can significantly contribute to the correct valuation of a company.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Jae Kwon Bae,