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A Rule-Based Model for Bankruptcy Prediction Based on an Improved Genetic Ant Colony Algorithm
Joint Authors
Zhang, Yudong
Wang, Shuihua
Ji, Genlin
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-28
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
In this paper, we proposed a hybrid system to predict corporate bankruptcy.
The whole procedure consists of the following four stages: first, sequential forward selection was used to extract the most important features; second, a rule-based model was chosen to fit the given dataset since it can present physical meaning; third, a genetic ant colony algorithm (GACA) was introduced; the fitness scaling strategy and the chaotic operator were incorporated with GACA, forming a new algorithm—fitness-scaling chaotic GACA (FSCGACA), which was used to seek the optimal parameters of the rule-based model; and finally, the stratified K-fold cross-validation technique was used to enhance the generalization of the model.
Simulation experiments of 1000 corporations’ data collected from 2006 to 2009 demonstrated that the proposed model was effective.
It selected the 5 most important factors as “net income to stock broker’s equality,” “quick ratio,” “retained earnings to total assets,” “stockholders’ equity to total assets,” and “financial expenses to sales.” The total misclassification error of the proposed FSCGACA was only 7.9%, exceeding the results of genetic algorithm (GA), ant colony algorithm (ACA), and GACA.
The average computation time of the model is 2.02 s.
American Psychological Association (APA)
Zhang, Yudong& Wang, Shuihua& Ji, Genlin. 2013. A Rule-Based Model for Bankruptcy Prediction Based on an Improved Genetic Ant Colony Algorithm. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-1032141
Modern Language Association (MLA)
Zhang, Yudong…[et al.]. A Rule-Based Model for Bankruptcy Prediction Based on an Improved Genetic Ant Colony Algorithm. Mathematical Problems in Engineering No. 2013 (2013), pp.1-10.
https://search.emarefa.net/detail/BIM-1032141
American Medical Association (AMA)
Zhang, Yudong& Wang, Shuihua& Ji, Genlin. A Rule-Based Model for Bankruptcy Prediction Based on an Improved Genetic Ant Colony Algorithm. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-1032141
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1032141