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A pre-processing and network analysis of GPS tracking data

机译:GPS跟踪数据的预处理和网络分析

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摘要

Global Positioning System (GPS) devices afford the opportunity to collect accurate data on unit movements from temporal and spatial perspectives. With a special focus on GPS technology in travel surveys, this paper proposes: (1) two algorithms for the pre-processing of GPS data in order to deal with outlier identification and missing data imputation; (2) a clustering approach to recover the main points of interest from GPS trajectories; and (3) a weighted-directed network, which incorporates the most relevant characteristics of the GPS trajectories at an aggregate level. A simulation study shows the goodness-of-fit of the imputation data algorithm and the robustness of the clustering algorithm. The proposed algorithms are then applied to three cases studies relating to the mobility of cruise passengers in urban contexts.
机译:全球定位系统(GPS)设备提供了从时间和空间视角下收集单位运动准确数据的机会。 在旅行调查中专注于GPS技术,本文提出了:(1)两个算法,用于预处理GPS数据,以处理异常识别和缺少数据归档; (2)恢复GPS轨迹的主要感兴趣点的聚类方法; (3)加权针对网络,其在骨料水平处包含GPS轨迹的最相关的特征。 仿真研究显示了归属数据算法的拟合和群集算法的鲁棒性。 然后将所提出的算法应用于三种案例研究与城市环境中邮轮乘客的流动性有关。

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