DocumentCode :
507986
Title :
Study of Financial Risk Prediction Based on Rough Set-ANN Model
Author :
Liu, Yanwen ; Zhou, Ming
Author_Institution :
Technol. Manage. Sch., Dalian Univ., Dalian, China
Volume :
2
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
444
Lastpage :
448
Abstract :
This article combines rough set and artificial neural network (ANN) which is improved with momentum accession and parameter self adaptive algorithm, and constructs a new financial risk prediction model. We apply this model to the empirical research on the financial risk prediction of some Chinese listed companies. Then we compared the outcome with the standard BP ANN, the results show that this combination model has higher prediction precision and efficiency than the traditional BP ANN model.
Keywords :
financial management; forecasting theory; neural nets; risk analysis; rough set theory; Chinese listed companies; artificial neural network; financial risk prediction; momentum accession; parameter self adaptive algorithm; rough set-ANN model; Adaptive algorithm; Artificial neural networks; Computer networks; Data mining; Data structures; Forward contracts; Predictive models; Risk analysis; Set theory; Technology management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.57
Filename :
5364397
Link To Document :
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