| 基于主成分分析-BP神经网络的道路客运站场布局决策研究 |
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| 引用本文： | 杨励雅,邵春福.基于主成分分析-BP神经网络的道路客运站场布局决策研究[J].城市发展研究,2008(Z1). |
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| 作者姓名： | 杨励雅 邵春福 |
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| 作者单位： | 中国人民大学公共管理学院;北京交通大学交通运输学院; |
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| 基金项目： | 中国人民大学科学研究基金项目(07XND012); 国家重点基础研究发展计划973项目(2006CB705500) |
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| 摘 要： | 为解决输入变量过多所造成的BP神经网络系统效率下降问题,提出一种主成分分析-BP神经网络的道路客运站场布局决策方法。首先,利用主成分分析方法,将个数较多的原始输入变量群变换为一组个数较少且彼此独立的新输入变量;然后,将新的输入变量群作为BP神经网络的输入进行道路客运站场的布局决策;最后,以廊坊市道路客运站场布局为例验证了方法的有效性。
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| 关 键 词： | 主成分分析 BP神经网络 站场布局 决策 |
A study on the BP neural network of road transport terminel leyout based on the principal componcnt anglysis |
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| Yang Liya,Shao Chunfu.A study on the BP neural network of road transport terminel leyout based on the principal componcnt anglysis[J].Urban Studies,2008(Z1). |
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| Authors: | Yang Liya Shao Chunfu |
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| Institution: | Yang Liya1,Shao Chunfu2(1.Renmin University of China,Beijing 1000872,2.Beijing Jiaotong University,Beijing 100044) |
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| Abstract: | A combined method is proposed to solve the layout of road passenger transport terminals in this paper.Principal Component Analysis was applied to gain the principal components of terminal layout,which can eliminate the correlation among previous indexes.The principal components were employed as the input variables of BP Neural Network,thus the problem of the inefficiency in BP Neural Network owing to excessive input variables has been solved.A practical example is also presented to validate the method. |
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| Keywords: | principal component analysis BP neural network terminal layout decision-making |
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