期刊論文
| 學年 | 94 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2006-02-01 |
| 作品名稱 | Financial Distress Prediction by a Radial Basis Function Network with Logit Analysis Learning |
| 作品名稱（其他語言） | |
| 著者 | 陳慶隆; Cheng, Chi-bin; Fu, Clay C. -J. |
| 單位 | 淡江大學會計學系 |
| 出版者 | |
| 著錄名稱、卷期、頁數 | Computers and Mathematics with Applications 51, pp.579-588 |
| 摘要 | This paper presents a financial distress prediction model that combines the approaches of neural network learning and logit analysis. This combination can retain the advantages and avoid the disadvantages of the two kinds of approaches in solving such a problem. The radial basis function network (RBFN) is adopted to construct the prediction model. The architecture of RBFN allows the grouping of similar firms in the hidden layer of the network and then performs a logit analysis on these groups instead of directly on the firms. Such a manner can remedy the problem of nominal variables in the input space. The performance of the proposed RBFN is compared to the traditional logit analysis and a backpropagation neural network and demonstrates superior results to both the counterparts in predictive accuracy for unseen data. |
| 關鍵字 | Financial distress prediction;Radial basis function network;Neural networks;Logit analysis |
| 語言 | en |
| ISSN | |
| 期刊性質 | 國內 |
| 收錄於 | |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | TWN |
| 公開徵稿 | |
| 出版型式 | ,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/64133 ) |