| 基于信令数据的人流时空分布和移动模式研究 |
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| 引用本文： | 黄建华,孟伟强,吴飞霞.基于信令数据的人流时空分布和移动模式研究[J].计算机工程与应用,2019,55(23):53-63. |
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| 作者姓名： | 黄建华 孟伟强 吴飞霞 |
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| 作者单位： | 华东理工大学 信息科学与工程学院,上海,200237;华东理工大学 信息科学与工程学院,上海,200237;华东理工大学 信息科学与工程学院,上海,200237 |
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| 摘 要： | 针对采用手机信令数据研究移动模式存在的数据稀疏、分布不均和信号漂移异常等问题，提出从数据量和数据分布两个层面解决数据稀疏和分布不均匀的数据预处理方法；提出基于主活动区域的人流时空分布算法来解决现有研究在考虑时段差异上的不足，并以上海市为例，对比分析了不同功能区在工作日和周末的人流时空分布规律；深入分析基于居住地的人类日常移动模式，提出了基于时空的栅格停留点抽取算法。实验结果表明该算法可以更准确地抽取出对用户有特殊意义的停留点，获取更简洁明了的用户移动模式。
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| 关 键 词： | 手机信令数据 时空分布 移动模式 |
Research of Human Flow Spatial-Temporal Distribution and Mobility Pattern Based on Signaling Data |
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| HUANG Jianhua,MENG Weiqiang,WU Feixia.Research of Human Flow Spatial-Temporal Distribution and Mobility Pattern Based on Signaling Data[J].Computer Engineering and Applications,2019,55(23):53-63. |
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| Authors: | HUANG Jianhua MENG Weiqiang WU Feixia |
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| Affiliation: | School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China |
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| Abstract: | Aiming at the problems of data sparseness, uneven distribution and abnormal signal drift in the mobility pattern studies based on mobile phone signaling data, this paper proposes a data preprocessing method to solve data sparseness and uneven distribution from two levels：data capacity and data distribution. A spatial and temporal distribution algorithm of the people flow based on main active area is used to solve the shortcomings of the existing researches in considering the difference of time slots. Taking Shanghai as an example, the spatial and temporal distribution of the people flow in different functional areas on weekdays and weekends is compared and analyzed. Finally, a stay point extraction algorithm based on grid which considers both space and time factors is proposed to study the daily mobility patterns of humans based on residence. The experimental results show that the algorithm can extract meaningful stay points for users more accurately and obtain more concise user mobility patterns. |
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| Keywords: | mobile phone signaling data spatial and temporal distribution mobility patterns |
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