Title :
A Hybrid GA-BP Model for Bankruptcy Prediction
Author :
Sai, Ying ; Zhong, Chenjian ; Qu, Lehong
Author_Institution :
Sch. of Comput. & Inf. Eng., Shandong Univ. of Finance, Jinan
Abstract :
With the increase of economic globalization and evolution of information technology, accounting information are being generated and accumulated at an unprecedented pace. As a result, there has been a critical need for automated approaches to effective and efficient utilization of massive amount of accounting information to support companies´ decision making. In this paper, we describe a hybrid GA-BP model in bankruptcy prediction. Optimization based on the genetic algorithm was executed on the neural networks thresholds and weights values. In addition, an example is given to validate the model; the results show our model has a high prediction accuracy in bankruptcy prediction
Keywords :
accounts data processing; backpropagation; decision making; genetic algorithms; neural nets; accounting information; backpropagation; bankruptcy prediction; decision making; economic globalization; genetic algorithm; information technology; neural networks; Accuracy; Artificial neural networks; Economic forecasting; Finance; Genetic algorithms; Neural networks; Neurons; Performance analysis; Power generation economics; Predictive models;
Conference_Titel :
Autonomous Decentralized Systems, 2007. ISADS '07. Eighth International Symposium on
Conference_Location :
Sedona, AZ
Print_ISBN :
0-7695-2804-X
DOI :
10.1109/ISADS.2007.3