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