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Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 31-883
Full Name: Jao-Hong Cheng
Position: Associate Professor
Age: ON
Sex: Male
Address: No.123, Sec. 3, Dasyue Road., Douliou City, Yulin Country, 640
Country: TAIWAN
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E-mail address: jhcheng@yuntech.edu.tw
Other E-mails: g9623802@yuntech.edu.tw
Title of the Paper: business failure prediction model based on grey prediction and rough set theory
Authors as they appear in the Paper: Jao-Hong Cheng, Huei-Ping Chen, Kai-Lun Cheng
Email addresses of all the authors: jhcheng@yuntech.edu.tw, g9623802@yuntech.edu.tw
Number of paper pages: 11
Abstract: A lot of methods have been used in the past for the prediction of failure business like Discriminant analysis, Logit analysis, Quadratic Function etc. Although some of these methods lead to models with a satisfactory ability to discriminate between healthy and bankrupt, they endure some limitations, often due to the unrealistic assumption of statistical hypotheses. This is why we have undertaken a hybrid advisable system aiming at weakening these limitations. A hybrid model that predicts the failure firms based on the past financial performance data, combining grey prediction and rough set approach is possible to predict using few data and quickly calculate. The results are very encouraging, compared with original rough set, and prove the usefulness and highlight the effectiveness of the proposed method for firm failure prediction.
Keywords: Grey Prediction, Rough Set Theory (RST), Business Failure, Financial Ratio
EXTENSION of the file: .doc
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