带反馈输入BP神经网络的应用研究

为了有效解决具有非线性特征的水文预报精准度的问题,通过对反向传播BP神经网络的学习和研究,分析了变量间的相互信息,提出了系统间相关信息熵的概念,并建立了适合水文预测的自迭代反向传播神经网络模型.该模型通过对迭代因子的及时修正,在反向传播中不断调整网络的权值和阈值,从而在很大程度上改善了传统BP算法所带来的不足,提高了预测的精度.实际的应用研究表明,自迭代反向传播模型的预测效果优于传统预测模型.

Applied research of BP neural network with feedback input

To effectively solve the accuracy problem of the hydrological forecasting with non-linear characteristics,by learning and researching the back-propagation BP neural network,analyzing the mutual information between the variables,the concept of the related information entropy between the systems is proposed,and a self-iterative back-propagation neural network model suitable for hydrological forecast is set up.This model improved the deficiency of the traditional BP algorithm greatly by correcting the iterativ...