《计算机应用研究》|Application Research of Computers

基于分段的移动对象轨迹简化算法

Segmentation-based trajectory simplification algorithm

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作者 张甜,杨智应
机构 上海海事大学 信息工程学院,上海 201306
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文章编号 1001-3695(2019)07-029-2044-05
DOI 10.19734/j.issn.1001-3695.2018.02.0090
摘要 GPS的高采样率使轨迹的数据规模巨大,在实际应用中难以处理,需要依赖轨迹简化算法对原始数据进行压缩。针对此问题,提出了一种新的基于速度分段的轨迹简化算法,即STS算法,在保留速度特征的同时保留了给定轨迹的时空特征。STS算法将速度值分组成若干间隔,将轨迹分割成速度保留段,计算各轨迹段的SED阈值,通过在每个子轨迹段上应用TD-TR算法导出简化的轨迹。通过真实的数据集进行广泛实验,验证所提出的算法比ATS算法具有更好的性能。
关键词 移动对象; 轮廓系数; TD-TR算法; 分类回归决策树; 轨迹简化
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本文URL http://www.arocmag.com/article/01-2019-07-029.html
英文标题 Segmentation-based trajectory simplification algorithm
作者英文名 Zhang Tian, Yang Zhiying
机构英文名 College of Information Engineering,Shanghai Maritime University,Shanghai 201306,China
英文摘要 The high sampling rate of GPS makes the data set of the trajectory huge, which is difficult to handle in practical applications. It needs to rely on trajectory simplification algorithm to compress the original data. Aiming at this problem, this paper proposed a new simplification algorithm based on speed segmentation, namely STS algorithm, which preserved the spatiotemporal characteristics while preserving the velocity characteristics of a given trajectory. The STS algorithm divided the velocity values into several intervals and divided the trajectory into velocity-preserving segments. It calculated the SED threshold of each trajectory segment and derived a simplified trajectory by applying the TD-TR algorithm on each sub-trajectory segment. Extensive experiments with real datasets demonstrate that the proposed algorithm has better performance than ATS algorithms.
英文关键词 moving object; silhouette coefficient; TD-TR algorithm; CART decision tree; trajectory simplification
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收稿日期 2018/2/23
修回日期 2018/4/4
页码 2044-2048
中图分类号 TP391
文献标志码 A