| 基于改进的BP人工神经网络的物流需求规模预测 |
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| 引用本文： | 陈治亚,周艾飞,谭钦之,方晓平.基于改进的BP人工神经网络的物流需求规模预测[J].铁道科学与工程学报,2008,5(6):62-68. |
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| 作者姓名： | 陈治亚 周艾飞 谭钦之 方晓平 |
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| 作者单位： | [1]中南大学交通运输工程学院,湖南长沙410075 [2]湘潭大学商学院,湖南湘潭411105 |
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| 基金项目： | 湖南省自然科学基金资助项目(07JJ3134); 中南大学2007年米塔尔学生创新创业项目(07MX11) |
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| 摘 要： | 为了对物流需求规模进行准确预测，探讨了用于物流需求规模预测的经济指标和物流需求规模的度量指标，再应用粗糙集理论、适应度函数和BP人工神经网络理论建立了用于物流需求规模预测的模型，即改进的BP人工神经网络模型。该模型首先应用粗糙集对BP人工神经网络的输入层进行指标知识约简，以减少BP人工神经网络的复杂度，再在BP人工神经网络中引入适应度函数，以克服传统BP人工神经网络算法易陷入局部最优、训练速度较慢等缺陷，最后，将该模型应用在案例分析中。结果表明，该模型使预测精度得到很大提高；该方法为以后物流需求规模的预测提供了一种新的思路和方法。
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| 关 键 词： | BP人工神经网络 粗糙集 适应度函数 物流需求规模 |
Forecasting model for the scale of logistics demand based on the improved back propagation artificial neural network |
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| CHEN Zhi-ya,ZHOU Ai-fei,TAN Qin-zhi,FANG Xiao-ping.Forecasting model for the scale of logistics demand based on the improved back propagation artificial neural network[J].Journal of Railway Science and Engineering,2008,5(6):62-68. |
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| Authors: | CHEN Zhi-ya ZHOU Ai-fei TAN Qin-zhi FANG Xiao-ping |
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| Abstract: | In order to forecast the scale of logistics demand,economic indicators which were appled to forecast the scale of logistics demand and the measuring indicator of the scale of logistics demand was studied.The rough set,the adaptation function and BP artificial neural network theory were applied to set up a model for forecasting the scale of logistics which was named the improved BP artificial neural network.The rough set was applied ill this model to reduce the number of indicators of the input layer in the ... |
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| Keywords: | back propagation artificial neural network(BP ANN) rough set adaptation function scale of logistics demand |
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