The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 53-398
Full Name: Hongbao Wang
Position: Assistant Professor
Age: ON
Sex: Female
Address: College of Applied English, Heilongjiang University, Harbin 150080, China
Country: CHINA
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E-mail address: tianzhihong@software.ict.ac.cn
Other E-mails: Lodgewang@163.com
Title of the Paper: Title A multi-level financial distress prediction model based on rough reduction and clustering
Authors as they appear in the Paper: Hongbao WANG, Fusheng WANG, Xiang YU
Email addresses of all the authors: Lodgewang@163.com
Number of paper pages: 10
Abstract: In order to improve the dynamic adaptability and predictive performance of the financial distress prediction model, this research proposed a multi-level financial distress prediction model based on rough reduction and clustering. This model improves predictive performance by the combination of an improved rough set attribute reduction method and the hierarchical clustering algorithm, BIRCH, which can process incremental data efficiently. Through attribute reduction by rough set, the influence of noisy data and redundant data were eliminated in order to identify the key indicators during the pre-processing phase. In the phase of FDP, the proposed multi-level model can deal with different application requirements so that different financial distress scenarios can be identified from various aspects. Empirical results with data from Chinese listed companies demonstrate that the model has a good dynamic adaptability and predictive performance..
Keywords: Financial distress prediction model; Clustering; Rough reduction
EXTENSION of the file: .doc
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