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基于改进BP神经网络的黑龙江农机总动力预测
引用本文:马海志,王福林,王慧鹏,何志连.基于改进BP神经网络的黑龙江农机总动力预测[J].农机化研究,2016(2):22-25,30.
作者姓名:马海志  王福林  王慧鹏  何志连
作者单位:东北农业大学工程学院,哈尔滨,150030
基金项目:国家社会科学基金项目(13BJY098)
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。

关 键 词:农机总动力  预测  BP算法  相对误差

Prediction of Total Power in Agriculture Machinery of Heilongjiang Based on An Improving Method o f BP Neural Network
Ma Haizhi;Wang Fulin;Wang Huipeng;He Zhilian.Prediction of Total Power in Agriculture Machinery of Heilongjiang Based on An Improving Method o f BP Neural Network[J].Journal of Agricultural Mechanization Research,2016(2):22-25,30.
Authors:Ma Haizhi;Wang Fulin;Wang Huipeng;He Zhilian
Institution:Ma Haizhi;Wang Fulin;Wang Huipeng;He Zhilian;College of Engineering,Northeast Agricultural University;
Abstract: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.
Keywords:total power of agriculture machinery  forecast  BP Neural Network  relative error
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