| 基于BP神经网络的城市货运生成预测模型 |
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| 引用本文： | 韦凌翔,董建军,陈志龙,赵峰.基于BP神经网络的城市货运生成预测模型[J].上海海事大学学报,2020,41(4):50-54. |
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| 作者姓名： | 韦凌翔 董建军 陈志龙 赵峰 |
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| 作者单位： | 盐城工学院材料科学与工程学院,江苏盐城224051;南京工业大学土木工程学院,南京211800;中国陆军工程大学国防工程学院,南京210007 |
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| 基金项目： | 国家自然科学基金(71631007，71601095) |
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| 摘 要： | 针对传统的货运生成模型处理非线性影响因素能力差的问题，运用BP神经网络建立城市货运生成多变量非线性预测模型。在对城市货运生成量影响因素进行分析的基础上，选取就业人数、地区GDP和消费品零售总额3个指标作为输入变量，以城市公路货运量和城市货运总量为输出变量，构建BP神经网络预测模型。该模型能揭示货运量与相关变量之间的非线性映射关系，在实证研究中取得了较理想的结果。通过实际货运量与BP神经网络预测结果的对比，验证了该模型在货运量预测方面的可行性。
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| 关 键 词： | 城市货运交通 货运生成 BP神经网络 |
| 收稿时间： | 2020/1/27 0:00:00 |
| 修稿时间： | 2020/3/26 0:00:00 |
Prediction model of urban freight generation based on BP neural network |
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| weilingxiang,DONG Jian-jun,CHEN Zhi-long and ZHAO Feng.Prediction model of urban freight generation based on BP neural network[J].Journal of Shanghai Maritime University,2020,41(4):50-54. |
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| Authors: | weilingxiang DONG Jian-jun CHEN Zhi-long and ZHAO Feng |
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| Institution: | Nanjing Tech University,Army Engineering University of PLA and Yancheng Institute of Technology |
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| Abstract: | Aiming at the problem of the poor ability of the traditional freight generation model to deal with the nonlinear influencing factors, the BP neural network is used to establish the multivariable nonlinear prediction model of the urban freight generation. Based on the analysis of the influencing factors of the urban freight generation volume, three indexes of the quantity of employment,the regional GDP and the total retail sales of consumer goods are selected as input variables, and the BP neural network prediction model is constructed with the output variables of the urban road freight volume and the urban total freight volume. By this model, the nonlinear mapping relationship between freight volume and related variables can be revealed, and ideal results are obtained in empirical research. By comparing the actual freight volume with the BP neural network prediction results, the feasibility of the model in the freight volume prediction is verified. |
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| Keywords: | urban freight traffic freight generation BP neural network |
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