[1]卞凤兰,黄晓明,刘睿.城镇化进程中公路网用地的BP神经网络预测模型[J].东南大学学报(自然科学版),2010,40(5):1073-1076.[doi:10.3969/j.issn.1001-0505.2010.05.036]
　Bian Fenglan,Huang Xiaoming,Liu Rui.BP neural network prediction model of highway network land in urbanization process[J].Journal of Southeast University (Natural Science Edition),2010,40(5):1073-1076.[doi:10.3969/j.issn.1001-0505.2010.05.036]
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城镇化进程中公路网用地的BP神经网络预测模型()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
40
期数:
2010年第5期
页码:
1073-1076
栏目:
交通运输工程
出版日期:
2010-09-20

文章信息/Info

Title:
BP neural network prediction model of highway network land in urbanization process
作者:
卞凤兰;  黄晓明;  刘睿
东南大学交通学院,南京 210096
Author(s):
Bian Fenglan;  Huang Xiaoming;  Liu Rui
School of Transportation, Southeast University, Nanjing 210096, China
关键词:
城镇化;  土地资源;  公路网用地;  BP神经网络;  预测
Keywords:
urbanization;  land resources;  land for highway network;  BP neural network;  prediction
分类号:
U412.1
DOI:
10.3969/j.issn.1001-0505.2010.05.036
摘要:
为了合理配置公路网用地,用BP神经网络的方法建立了城镇化进程中公路网用地的预测模型.首先通过分析公路网对城镇化进程的影响,阐明了合理的公路网用地在城镇化进程中的重要性.在用BP神经网络建模的过程中,输入层的神经元采用城镇化率及城镇占地比,输出层的神经元采用公路占地比; 根据城镇化水平和公路网发展情况选用德国等7国数据作为1号训练样本,根据土地资源情况选用日本数据作为2号训练样本; 预测时可用本区域的历史数据作为3号训练样本; 通过MATLAB进行编程运算.最后根据安徽省数据对模型进行了实证分析.BP神经网络预测模型克服了传统线性模型的不足,考虑了土地资源对公路网用地的约束,能够对不同城镇化水平的公路网用地进行预测.
Abstract:
To collocate the land for the highway network reasonably, a prediction model using the BP(back propagation)neural network has been created. Based on the analysis of the effect of highway network in the urbanization process, the importance of planning reasonable lands of the road network in the process of urbanization is clarified. In the modeling process using BP neural network, the urbanization rate and the proportion of urban land area are used as the neurons of the input layer, and the proportion of highway land area is used as the neuron of the output layer. The data of seven western countries are chosen as No.1 training sample according to the situation of urbanization level and highway development, and the historical data from Japan are chosen as No.2 training sample according to the situation of land resources. The historical data from the region can be used as No.3 training sample in the prediction model. The operation procedure is designed by MATLAB. Finally, the model is proved by using the data from Anhui province. The model considers the constraint of land resources to the land for highway network and overcome the deficiencies of the traditional linear model. The model presented in this paper can be used to predict the land for highway network under different levels of urbanization.

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备注/Memo

备注/Memo:
作者简介: 卞凤兰(1968—),女,博士生; 黄晓明(联系人),男,博士,教授,博士生导师,huangxm@seu.edu.cn.
引文格式: 卞凤兰,黄晓明,刘睿.城镇化进程中公路网用地的BP神经网络预测模型[J].东南大学学报:自然科学版,2010,40(5):1073-1076. [doi:10.3969/j.issn.1001-0505.2010.05.036]
更新日期/Last Update: 2010-09-20