Results 21 to 30 of about 1,061,883 (288)
Ordering of trajectories reveals hierarchical finite-time coherent sets in Lagrangian particle data: detecting Agulhas rings in the South Atlantic Ocean [PDF]
Nonlinear Processes in Geophysics, 2021 The detection of finite-time coherent particle sets in Lagrangian trajectory data, using data-clustering techniques, is an active research field at the moment.
D. Wichmann +6 more
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A Clustering Ensemble Method of Aircraft Trajectory Based on the Similarity Matrix
Aerospace, 2022 Performing clustering analysis on a large amount of historical trajectory data can obtain information such as frequent flight patterns of aircraft and air traffic flow distribution, which can provide a reference for the revision of standard flight ...
Xiao Chu, Xianghua Tan, Weili Zeng
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Applied Sciences, 2023 Trajectory clustering algorithms analyze the movement trajectory of the target objects to mine the potential movement trend, regularity, and behavioral patterns of the object.
Xiaoya An +6 more
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Evolutionary Clustering of Streaming Trajectories
CoRR, 2021 The widespread deployment of smartphones and location-enabled, networked in-vehicle devices renders it increasingly feasible to collect streaming trajectory data of moving objects. The continuous clustering of such data can enable a variety of real-time services, such as identifying representative paths or common moving trends among objects in real ...
Tianyi Li 0005 +4 more
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Trajectory clustering for motion prediction [PDF]
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012 We investigate a data-driven approach to robotic path planning and analyze its performance in the context of interception tasks. Trajectories of moving objects often contain repeated patterns of motion, and learning those patterns can yield interception paths that succeed more often.
Sung, Cynthia +2 more
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Incremental Clustering for Trajectories [PDF]
, 2010 Trajectory clustering has played a crucial role in data analysis since it reveals underlying trends of moving objects. Due to their sequential nature, trajectory data are often received incrementally, e.g., continuous new points reported by GPS system. However, since existing trajectory clustering algorithms are developed for static datasets, they are ...
Li, Z. Li, Zhenhui +3 more
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A Hybrid-Clustering Model of Ship Trajectories for Maritime Traffic Patterns Analysis in Port Area
Journal of Marine Science and Engineering, 2022 A hybrid-clustering model is presented for the probabilistic characterization of ship traffic and anomaly detection. A hybrid clustering model was proposed to increase the efficiency of trajectory clustering in the port area and analyze the maritime ...
Lei Liu +5 more
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An Improved Fuzzy Trajectory Clustering Method for Exploring Urban Travel Patterns
Journal of Advanced Transportation, 2021 Exploring urban travel patterns can analyze the mobility regularity of residents to provide guidance for urban traffic planning and emergency decision.
Fang Liu +4 more
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Trajectory Clustering Algorithm Based on Group and Density [PDF]
Jisuanji gongcheng, 2021 The existing density-based clustering methods are mainly used for point data clustering, and not suitable for large-scale trajectory data. To address the problem, this paper proposes a trajectory clustering algorithm based on group and density. According
YU Qingying, ZHAO Yajun, YE Zitong, HU Fan, XIA Yun
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Application of OPTICS and Offline Batch Processing in Trajectory Clustering [PDF]
Jisuanji gongcheng, 2020 Trajectory clustering is an important step in spatio-temporal trajectory processing.Common trajectory clustering algorithms,such as TRACLUS algorithm,usually have high time complexity and are sensitive to input parameters,thus consuming a lot of time to ...
GUO Yu, CHEN Jinyong, ZHANG Xinyu, LI Liang, SUN Weiwei
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