摘要
BP神经网络在人工神经网络中起着至关重要的作用,通过分析标准BP神经网络的基本算法,指出标准BP算法的一些不足,并针对这些不足提出了以一种以相对误差作为误差传递信号的新的改进方法。经试验证明:该方法大大提高了BP神经网络预测结果的精度,同时这种新的改进思想也可以结合其他改进方法一起应用,以更大程度上地提高BP神经网络的运算速度和预测精度。
BP neural network plays a vital role in artificial neural networks.In this paper, through the analysis of the basic algorithm of standard BP neural network, and points out some shortcomings of the standard BP algorithm, to solve these problems we use a relative error as a new improved method of error transfer signal .The test proved that this method greatly improves the accuracy of BP neural network prediction, and this new and improved idea can also be applied to-gether with other improved methods to predict the computing speed and accuracy to a greater extent to improve BP neural network.
出处
《农机化研究》
北大核心
2016年第2期22-25 30,30,共5页
Journal of Agricultural Mechanization Research
基金
国家社会科学基金项目(13BJY098)
关键词
农机总动力
预测
BP算法
相对误差
total power of agriculture machinery
forecast
BP Neural Network
relative error