Back Propagation Neural Network And Applications

Artificial Neural Network, a new but hot cross discipline, enjoys quite a great prospect of application. With its many characteristics such as large-scale parallel information processing, excellent self-adaptation and self-learning, the Network has been used in solving the complex nonlinear dynamic system prediction. The prediction study based on ANN is a important problem, enjoys significance in theory and reality.This paper has at chart one introduced the Network' s history of development, its fields of application and then characteristics as well as the few typical neural networks used widely at present. At chart two and chart three, it has focused its research on the problems of back-propagation (BP) network structure, algorithms principle and convergence. At chart four, it has analytically discussed some of the problems that lie in BP Neural Network. In view of the flaws in BP Neural Network, the paper has introduced some improved BP algorithms and forwarded ones. At chart five, this paper applied it to the assessment of urban environmental quality, built a BP model, normalized the given data and decided the hide codes and parameters such as momentum and learn rate, and so on. At the same time, a assessment system of urban environmental quality based on ANN has designed with Visual FoxPro 6.0. The results of application show that the arithmetic is of high speed for convergence and of high accuracy for prediction and therefore meets with actual requirements of application and is an effective predictive method. This assessment system may be applied to the related assessment.