Hybrid Neural Network Based on GA-BP for Personal Credit Scoring

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.