DocumentCode
2808579
Title
Genetic Neural Network Model of Forecasting Financial Distress of Listed Companies
Author
Xinli, Wang
Author_Institution
Sch. of Econ. & Manage., North China Electr. Power Univ., Baoding, China
Volume
1
fYear
2011
fDate
26-27 Nov. 2011
Firstpage
487
Lastpage
490
Abstract
This paper uses the global optimization of genetic algorithm to construct a genetic neural network model (GANN) forecasting listed company financial crisis. The model optimizes input variables of neural network model forecasting financial crisis. Forecasting of financial distress of listed companies in Shanghai and Shenzhen A share markets indicates that this model bears a better ability to predict financial distress compared with ANN model.
Keywords
economic forecasting; financial management; genetic algorithms; neural nets; GANN forecasting; Shanghai; Shenzhen; financial distress forecasting; genetic algorithm; genetic neural network model; global optimization; listed company financial crisis; neural network model forecasting; Analytical models; Artificial neural networks; Companies; Computational modeling; Forecasting; Predictive models; Training; Financial distress; Genetic algorithm; Neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Management, Innovation Management and Industrial Engineering (ICIII), 2011 International Conference on
Conference_Location
Shenzhen
Print_ISBN
978-1-61284-450-3
Type
conf
DOI
10.1109/ICIII.2011.124
Filename
6115054
Link To Document