Skip to main navigation Skip to search Skip to main content

Hybrid neural network based on GA-BP for personal credit scoring

  • Wang Shulin*
  • , Yin Shuang
  • , Jiang Minghui
  • *Corresponding author for this work
  • School of Management, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Aiming at the insufficiencies of BP neural network, this paper established a hybrid neural network based on the combination of GA and BP algorithms. The hybrid algorithm made fully use of GA's global searching to improve the learning ability of neural network with the combination of BP. The model was used in personal credit scoring in commercial banks. Compared with single BP neural network, the training results of hybrid neural network indicate that the hybrid algorithm can improve the learning ability of neural network to achieve the training goal. The classification accuracy of hybrid neural network on testing samples is higher than that of single BP neural network.

Original languageEnglish
Title of host publicationProceedings - 4th International Conference on Natural Computation, ICNC 2008
Pages209-214
Number of pages6
DOIs
StatePublished - 2008
Externally publishedYes
Event4th International Conference on Natural Computation, ICNC 2008 - Jinan, China
Duration: 18 Oct 200820 Oct 2008

Publication series

NameProceedings - 4th International Conference on Natural Computation, ICNC 2008
Volume3

Conference

Conference4th International Conference on Natural Computation, ICNC 2008
Country/TerritoryChina
CityJinan
Period18/10/0820/10/08

Fingerprint

Dive into the research topics of 'Hybrid neural network based on GA-BP for personal credit scoring'. Together they form a unique fingerprint.

Cite this