| 基于时空数据挖掘的铁路客流预测方法 |
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| 引用本文： | 徐薇,黄厚宽,秦勇.基于时空数据挖掘的铁路客流预测方法[J].北京交通大学学报(自然科学版),2004,28(5):16-19. |
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| 作者姓名： | 徐薇 黄厚宽 秦勇 |
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| 作者单位： | 北京交通大学,计算机与信息技术学院,北京,100044;中国铁道科学研究院,电子所,北京,100081 |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | 提出了一种新的基于时空数据挖掘的铁路客流预测方法,该方法一方面采用统计学原理对目标对象本身的时序进行预测,另一方面通过神经网络解算相邻对象的空间影响,最后使用线性回归得到综合预测结果.采用该方法对某铁路直通区段2004年春运期间旅客总发送量进行预测,与不考虑空间影响的预测方法相比,预测精度有所改善.
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| 关 键 词： | 铁路运输 客流预测 时空预测 时空数据挖掘 |
| 文章编号： | 1673-0291(2004)05-0016-04 |
| 修稿时间： | 2003年7月10日 |
Study of Railway Passenger Flow Forecasting Method Based on Spatio-Temporal Data Mining |
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| XU Wei,HUANG Hou-kuan,QIN Yong.Study of Railway Passenger Flow Forecasting Method Based on Spatio-Temporal Data Mining[J].JOURNAL OF BEIJING JIAOTONG UNIVERSITY,2004,28(5):16-19. |
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| Authors: | XU Wei HUANG Hou-kuan QIN Yong |
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| Institution: | XU Wei~1,HUANG Hou-kuan~1,QIN Yong~2 |
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| Abstract: | By analyzing the limitation of current passenger flow forecast approach, this paper presents a new approach to forecast railway passenger flow based on spatio_temporal data mining. The approach first forecasts time sequence of target object using statistical principles, then figures out the spatial influence of neighbor objects using a neural network, and finally combines the two forecasting results using linear regression. The method is used in the forecast of railway passenger flow during the spring festival period in 2004. Comparing with the existing approaches that don't consider the spatial influence, the forecast accuracy of our approach is better. |
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| Keywords: | railway transportation passenger flow forecast spatio-temporal forecast spatio-temporal data mining |
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