DocumentCode :
479662
Title :
Electric power enterprise financial risk evaluation based on Rough Set and BP network
Author :
Lin, Zhihong ; Qiao, Hong ; Dong, Xuechen
Author_Institution :
Economic Manage. Dept., North China Electr. Power Univ., Baoding
Volume :
1
fYear :
2008
fDate :
12-15 Oct. 2008
Firstpage :
954
Lastpage :
958
Abstract :
The comprehensive evaluation problem of electric power listed corporation has always been a focus since market-oriented reform of the electric power industry, and financial risk evaluation play a key role to science investment decision of electric power listed corporation .This paper presents a new composite forecasting method for financial risk of electric power corporation, modeling and forecasting based on rough set and back-propagation neural network model. Combing reality financial data of electric power listed corporation and using rough set theory to select financial indexes, which are as modeling variables, then establishing financial risk estimation model based on Back-propagation neural network. Through training for the financial data, it shows that this model has a high accuracy to the results of financial risks evaluation, and it offers effective technical support to financial risk evading of electric power enterprise.
Keywords :
backpropagation; financial management; investment; neural nets; power engineering computing; power markets; risk management; rough set theory; BP neural network model; backpropagation neural network model; composite forecasting method; electric power industry; financial risk estimation model; investment decision; market-oriented reform; rough set theory; Biological neural networks; Brain modeling; Economic forecasting; Energy management; Financial management; Neural networks; Power generation economics; Predictive models; Risk management; Set theory; BP network; electric power enterprise; financial risk; rough set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Service Operations and Logistics, and Informatics, 2008. IEEE/SOLI 2008. IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2012-4
Electronic_ISBN :
978-1-4244-2013-1
Type :
conf
DOI :
10.1109/SOLI.2008.4686536
Filename :
4686536
Link To Document :
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