Title :
An Application of Improved BP Neural Network in Personal Credit Scoring
Author :
Qin, Rui ; Liu, Lie Li ; Xie, Jun
Author_Institution :
Sch. of Econ. & Manage., Beihang Univ., Beijing, China
Abstract :
Personal Credit Scoring is of great significance for commercial banks to circumvent credit consumption, the original BP algorithm´s convergence rate is slow, learning precision is low, the training process is easy to fall into local minimum, this paper presents an improved algorithm with variable learning rate based on BP algorithm, and applied to simulate personal credit scoring. After comparing we found the improved algorithm has greatly reduced the network´s number of iterations, shorten the network training time and improved the training accuracy.
Keywords :
backpropagation; financial data processing; learning (artificial intelligence); neural nets; circumvent credit consumption; commercial banks; improved BP neural network; network training time; personal credit scoring; variable learning rate; Application software; Computational modeling; Computer network management; Computer networks; Computer simulation; Conference management; Convergence; Electronic mail; Management training; Neural networks; BP Algorithm; Dynamic Learning Rate; Neural Networks; Personal Credit Scoring;
Conference_Titel :
Computer Modeling and Simulation, 2010. ICCMS '10. Second International Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-1-4244-5642-0
Electronic_ISBN :
978-1-4244-5643-7
DOI :
10.1109/ICCMS.2010.147
