A Novel Ensemble Learning Approach for Corporate Financial Distress Forecasting in Fashion and Textiles Supply Chains
Joint Authors
Xie, Gang
Zhao, Yingxue
Jiang, Mao
Zhang, Ning
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-03-11
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This paper proposes a novel ensemble learning approach based on logistic regression (LR) and artificial intelligence tool, that is, support vector machine (SVM) and back-propagation neural networks (BPNN), for corporate financial distress forecasting in fashion and textiles supply chains.
Firstly, related concepts of LR, SVM, and BPNN are introduced.
Then, the forecasting results by LR are introduced into the SVM and BPNN techniques which can recognize the forecasting errors in fitness by LR.
Moreover, empirical analysis of Chinese listed companies in fashion and textile sector is implemented for the comparison of the methods, and some related issues are discussed.
The results suggest that the proposed novel ensemble learning approach can achieve higher forecasting performance than those of individual models.
American Psychological Association (APA)
Xie, Gang& Zhao, Yingxue& Jiang, Mao& Zhang, Ning. 2013. A Novel Ensemble Learning Approach for Corporate Financial Distress Forecasting in Fashion and Textiles Supply Chains. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1031928
Modern Language Association (MLA)
Xie, Gang…[et al.]. A Novel Ensemble Learning Approach for Corporate Financial Distress Forecasting in Fashion and Textiles Supply Chains. Mathematical Problems in Engineering No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-1031928
American Medical Association (AMA)
Xie, Gang& Zhao, Yingxue& Jiang, Mao& Zhang, Ning. A Novel Ensemble Learning Approach for Corporate Financial Distress Forecasting in Fashion and Textiles Supply Chains. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1031928
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1031928