| 基于广义回归神经网络的铁路货运量预测 |
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| 引用本文： | 温爱华,李松.基于广义回归神经网络的铁路货运量预测[J].铁道运输与经济,2011,33(2):88-91. |
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| 作者姓名： | 温爱华 李松 |
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| 作者单位： | 1. 河北软件职业技术学院,信息工程系,河北,保定,071000
2. 河北大学,管理学院,河北,保定,071002 |
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| 摘 要： | 针对BP神经网络预测存在局部极小缺陷和收敛速度慢的问题,提出基于广义回归神经网络(GRNN)的预测模型。基于我国1999—2008年铁路货运量的历史统计数据,应用GRNN模型和混沌BP神经网络模型对铁路货运量进行预测。通过两种预测模型的计算结果比较说明,GRNN模型具有良好的收敛性和较高的精度,而且模型结构简单、计算速度快,具有良好的实用性。
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| 关 键 词： | 铁路 货运量预测 GRNN模型 BP模型 |
Forecast of Railway Freight Volumes Based on Generalized Regression Neural Network |
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| WEN Ai-hua,LI Song.Forecast of Railway Freight Volumes Based on Generalized Regression Neural Network[J].Rail Way Transport and Economy,2011,33(2):88-91. |
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| Authors: | WEN Ai-hua LI Song |
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| Institution: | WEN Ai-hua1,LI Song2(1 Department of Information Engineering,Hebei Software Institute,Baoding 071000,Hebei,China,2 School of Management,Hebei University,Baoding 071002,China) |
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| Abstract: | Aiming at the problems of BP neural network on local small objection and slow convergence speed,this paper puts forward the forecasting model based on generalized regression neural network(GRNN).Based on the historical statistic data of Chinese railway freight traffic volume in 1999-2008,the paper makes forecast on railway freight traffic volume by using GRNN model and chaos BP neutral network.Through comparison on the calculation results of these two forecast models,the paper illuminates that the GRNN mode... |
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| Keywords: | Railway Forecast of Railway Freight Volume Generalized Regression Neural Network(GRNN) BP Model |
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