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Gotowe bibliografie tematyczne / Temporal-constrained (sub-)trajectory clustering

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Gotowa bibliografia na temat „Temporal-constrained (sub-)trajectory clustering”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Temporal-constrained (sub-)trajectory clustering"

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Cheng, Xiaoqian, Chengming Li, Weibing Du, Jianming Shen, and Zhaoxin Dai. "Trip Extraction of Shared Electric Bikes Based on Multi-Rule-Constrained Homomorphic Linear Clustering Algorithm." ISPRS International Journal of Geo-Information 8, no. 12 (2019): 526. http://dx.doi.org/10.3390/ijgi8120526.

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Trajectory data include rich interactive information of humans. The correct identification of trips is the key to trajectory data mining and its application. A new method, multi-rule-constrained homomorphic linear clustering (MCHLC), is proposed to extract trips from raw trajectory data. From the perspective of the workflow, the MCHLC algorithm consists of three parts. The first part is to form the original sub-trajectory moving/stopping clusters, which are obtained by sequentially clustering trajectory elements of the same motion status. The second part is to determine and revise the motion s

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Guo, Yishan, and Mandan Liu. "Spatial-temporal trajectory anomaly detection based on an improved spectral clustering algorithm." Intelligent Data Analysis 27, no. 1 (2023): 31–58. http://dx.doi.org/10.3233/ida-216185.

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With the development of wireless communication technology, when users use wireless networks to meet various needs, wireless networks also record a large number of users’ spatial-temporal trajectory data. In order to better pay attention to the healthy development of students and promote the information construction on campus, a spectral clustering algorithm based on the multi-scale threshold and density combined with shared nearest neighbors (MSTDSNN-SC) is proposed. Firstly, it improves the affinity distance function based on the shortest time dis-tance-shortest time distance sub-sequence (ST

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Dritsas, Elias, Andreas Kanavos, Maria Trigka, Spyros Sioutas, and Athanasios Tsakalidis. "Storage Efficient Trajectory Clustering and k-NN for Robust Privacy Preserving Spatio-Temporal Databases." Algorithms 12, no. 12 (2019): 266. http://dx.doi.org/10.3390/a12120266.

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The need to store massive volumes of spatio-temporal data has become a difficult task as GPS capabilities and wireless communication technologies have become prevalent to modern mobile devices. As a result, massive trajectory data are produced, incurring expensive costs for storage, transmission, as well as query processing. A number of algorithms for compressing trajectory data have been proposed in order to overcome these difficulties. These algorithms try to reduce the size of trajectory data, while preserving the quality of the information. In the context of this research work, we focus on

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Yang, Jinhao, Junwen Cao, and Mingyu Fang. "Personalized trajectory inference framework integrating driving behavior recognition and temporal dependency learning." PLOS One 20, no. 7 (2025): e0326937. https://doi.org/10.1371/journal.pone.0326937.

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This study proposes a Driving style-Tri Channel Trajectory Model (DS-TCTM) to enhance vehicle trajectory prediction accuracy and driving safety. The framework operates through three rigorously designed stages: (1)Data preprocessing involving kinematics feature extraction, (2)Driving style recognition utilizing acceleration variation rate and average time headway combined with K-Means++ traffic density clustering and K-neighbor Gaussian mixture model (K-GMM) analysis to classify driving behaviors into conservative, moderate, and radical categories, and (3)Personalized trajectory prediction empl

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Pelekis, Nikos, Panagiotis Tampakis, Marios Vodas, Christos Doulkeridis, and Yannis Theodoridis. "On temporal-constrained sub-trajectory cluster analysis." Data Mining and Knowledge Discovery 31, no. 5 (2017): 1294–330. http://dx.doi.org/10.1007/s10618-017-0503-4.

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Liu, C. K., K. Qin, K. Chen, and R. Ma. "UNCOVERING THE AGGREGATION PATTERN OF GPS TRAJECTORY BASED ON SPATIOTEMPORAL CLUSTERING AND 3D VISUALIZATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W10 (February 7, 2020): 255–60. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w10-255-2020.

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Abstract. Constrained by road network structure, travel choice and city function zoning, GPS trajectory data exhibits significant spatiotemporal correlation. Unveiling the clustering and distribution patterns of GPS trajectory can help to better understand the travel behaviour as well as the corresponding spatial and temporal characteristics. This paper proposes an approach to identify and visualize the aggregation pattern from GPS trajectory data. Firstly, slow feature trajectory sequences are extracted from raw taxi trajectory data. Together with taxi states information, these sequences are

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Zhao, Yinan, Tao Liu, Xiang Feng, Zhanfeng Zhao, Wenqing Cui, and Yu Fan. "New Application: A Hand Air Writing System Based on Radar Dual View Sequential Feature Fusion Idea." Remote Sensing 14, no. 20 (2022): 5177. http://dx.doi.org/10.3390/rs14205177.

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In recent years, non-contact human–computer interactions have aroused much attention. In this paper, we mainly propose a dual view observation system based on the frontal and side millimeter-wave radars (MWR) to collect echo data of the Air writing digits “0~9”, simultaneously. Additionally, we also propose a novel distance approximation method to make the trajectory reconstruction more efficient. To exploit these characteristics of spatial-temporal adjacency in handwriting digits, we propose a novel clustering algorithm, named the constrained density-based spatial clustering of application wi

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Matos, Tiago R., Hongye Liu, Masahiro Hirakawa, Ana Cristina Alho, and Jerome Ritz. "Maturation and Phenotypic Diversity of Human CD4+ Regulatory T Cells in Umbilical Cord Blood and Peripheral Blood from Healthy Donors." Blood 126, no. 23 (2015): 2357. http://dx.doi.org/10.1182/blood.v126.23.2357.2357.

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Abstract Introduction: CD4+ FoxP3+ CD25+ regulatory T cells (Treg) are required for maintenance of immune tolerance and immune homeostasis. Quantitative or functional Treg deficiency has been correlated with autoimmune disease, allergy, allograft rejection and graft versus host disease. Conversely, increased Treg can suppress tumor immunity resulting in tumor progression. Treg express a large number of cellular markers that reflect their level of maturation, functionality, activation and migratory capacity. Nevertheless, it has not previously been possible to integrate the expression of these

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de Foy, B., W. Lei, M. Zavala, et al. "Modelling constraints on the emission inventory and on vertical diffusion for CO and SO<sub>2</sub> in the Mexico City Metropolitan Area using Solar FTIR and zenith sky UV spectroscopy." Atmospheric Chemistry and Physics Discussions 6, no. 4 (2006): 6125–81. http://dx.doi.org/10.5194/acpd-6-6125-2006.

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Abstract. Emissions of air pollutants in and around urban areas lead to negative health impacts on the population. To estimate these impacts, it is important to know the sources and transport mechanisms of the pollutants accurately. Mexico City has a large urban fleet in a topographically constrained basin leading to high levels of carbon monoxide (CO). Large point sources of sulfur dioxide (SO2) surrounding the basin lead to episodes with high concentrations. An Eulerian grid model (CAMx) and a particle trajectory model (FLEXPART) are used to evaluate the estimates of CO and SO2 in the curren

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de Foy, B., W. Lei, M. Zavala, et al. "Modelling constraints on the emission inventory and on vertical dispersion for CO and SO<sub>2</sub> in the Mexico City Metropolitan Area using Solar FTIR and zenith sky UV spectroscopy." Atmospheric Chemistry and Physics 7, no. 3 (2007): 781–801. http://dx.doi.org/10.5194/acp-7-781-2007.

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Abstract. Emissions of air pollutants in and around urban areas lead to negative health impacts on the population. To estimate these impacts, it is important to know the sources and transport mechanisms of the pollutants accurately. Mexico City has a large urban fleet in a topographically constrained basin leading to high levels of carbon monoxide (CO). Large point sources of sulfur dioxide (SO2) surrounding the basin lead to episodes with high concentrations. An Eulerian grid model (CAMx) and a particle trajectory model (FLEXPART) are used to evaluate the estimates of CO and SO2 in the curren

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