Artigos de revistas sobre o tema "Trafic spatial"
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Pogorelov, A. V., K. R. Golovan e M. V. Kuzyakina. "SPATIAL STRUCTURE OF INTERNET-TRAFIC CONSUMPTION IN THE MTS NETWORK IN A LARGE CITY (BASED ON KRASNODAR DATA)". Proceedings of the International conference “InterCarto/InterGIS” 1, n.º 21 (1 de janeiro de 2015): 548–52. http://dx.doi.org/10.24057/2414-9179-2015-1-21-548-552.
Texto completo da fonteLiu, Shaohua, Shijun Dai, Jingkai Sun, Tianlu Mao, Junsuo Zhao e Heng Zhang. "Multicomponent Spatial-Temporal Graph Attention Convolution Networks for Traffic Prediction with Spatially Sparse Data". Computational Intelligence and Neuroscience 2021 (23 de dezembro de 2021): 1–12. http://dx.doi.org/10.1155/2021/9134942.
Texto completo da fonteZhang, Shen, Jinjun Tang, Hua Wang e Yinhai Wang. "Enhancing Traffic Incident Detection by Using Spatial Point Pattern Analysis on Social Media". Transportation Research Record: Journal of the Transportation Research Board 2528, n.º 1 (janeiro de 2015): 69–77. http://dx.doi.org/10.3141/2528-08.
Texto completo da fonteTanner, John. "Urban spatial traffic patterns". Transportation Research Part A: General 24, n.º 5 (setembro de 1990): 397–98. http://dx.doi.org/10.1016/0191-2607(90)90052-8.
Texto completo da fonteLi, Tian, Mengmeng Zhang, Haobin Jiang e Peng Jing. "Understanding the Modifiable Areal Unit Problem and Identifying Appropriate Spatial Units while Studying the Influence of the Built Environment on the Traffic System State". Journal of Advanced Transportation 2022 (14 de setembro de 2022): 1–11. http://dx.doi.org/10.1155/2022/8288248.
Texto completo da fonteLiao, Wanying, Hongtao Wang e Jiajun Xu. "The Spatial Structure Characteristic and Road Traffic Accessibility Evaluation of A-Level Tourist Attractions within Wuhan Urban Agglomeration in China". 3C Tecnología_Glosas de innovación aplicadas a la pyme 12, n.º 2 (25 de junho de 2023): 388–409. http://dx.doi.org/10.17993/3ctecno.2023.v12n3e45.388-409.
Texto completo da fonteYAMAGUCHI, Hiromichi, e Makoto OKUMURA. "1C33 Temporal and Spatial Differences of Leisure Travel Frequency Distribution in Japan(Traffic Planning)". Proceedings of International Symposium on Seed-up and Service Technology for Railway and Maglev Systems : STECH 2015 (2015): _1C33–1_—_1C33–12_. http://dx.doi.org/10.1299/jsmestech.2015._1c33-1_.
Texto completo da fonteBraxmeier, Hans, Volker Schmidt e Evgueni Spodarev. "SPATIAL EXTRAPOLATION OF ANISOTROPIC ROAD TRAFFIC DATA". Image Analysis & Stereology 23, n.º 3 (3 de maio de 2011): 185. http://dx.doi.org/10.5566/ias.v23.p185-198.
Texto completo da fontePavlyuk, Dmitry. "Temporal Aggregation Effects in Spatiotemporal Traffic Modelling". Sensors 20, n.º 23 (4 de dezembro de 2020): 6931. http://dx.doi.org/10.3390/s20236931.
Texto completo da fonteXiong, Liyan, Weihua Ding, Xiaohui Huang e Weichun Huang. "CLSTAN: ConvLSTM-Based Spatiotemporal Attention Network for Traffic Flow Forecasting". Mathematical Problems in Engineering 2022 (11 de julho de 2022): 1–13. http://dx.doi.org/10.1155/2022/1604727.
Texto completo da fontePavlyuk. "Transfer Learning: Video Prediction and Spatiotemporal Urban Traffic Forecasting". Algorithms 13, n.º 2 (13 de fevereiro de 2020): 39. http://dx.doi.org/10.3390/a13020039.
Texto completo da fonteFeng, Jian, Lang Yu e Rui Ma. "AGCN-T: A Traffic Flow Prediction Model for Spatial-Temporal Network Dynamics". Journal of Advanced Transportation 2022 (29 de maio de 2022): 1–12. http://dx.doi.org/10.1155/2022/1217588.
Texto completo da fonteTassadit Dial, Rania, e Gabriel Figueiredo De Oliveira. "Accessibilité à l’arrière-pays, connectivité maritime et relations interportuaires : une analyse spatiale". Revue d’Économie Régionale & Urbaine Octobre, n.º 4 (19 de outubro de 2023): 579–607. http://dx.doi.org/10.3917/reru.234.0579.
Texto completo da fonteKumar, Dr T. Senthil. "Video based Traffic Forecasting using Convolution Neural Network Model and Transfer Learning Techniques". Journal of Innovative Image Processing 2, n.º 3 (17 de junho de 2020): 128–34. http://dx.doi.org/10.36548/jiip.2020.3.002.
Texto completo da fonteGao, Jingqin, Kun Xie e Kaan Ozbay. "Exploring the Spatial Dependence and Selection Bias of Double Parking Citations Data". Transportation Research Record: Journal of the Transportation Research Board 2672, n.º 42 (18 de agosto de 2018): 159–69. http://dx.doi.org/10.1177/0361198118792323.
Texto completo da fonteKošanin, Ivan, Milan Gnjatović, Nemanja Maček e Dušan Joksimović. "A Clustering-Based Approach to Detecting Critical Traffic Road Segments in Urban Areas". Axioms 12, n.º 6 (24 de maio de 2023): 509. http://dx.doi.org/10.3390/axioms12060509.
Texto completo da fonteAbduljabbar, Rusul, Hussein Dia, Pei-Wei Tsai e Sohani Liyanage. "Short-Term Traffic Forecasting: An LSTM Network for Spatial-Temporal Speed Prediction". Future Transportation 1, n.º 1 (30 de março de 2021): 21–37. http://dx.doi.org/10.3390/futuretransp1010003.
Texto completo da fonteChang, Zhihong, Chunsheng Liu e Jianmin Jia. "STA-GCN: Spatial-Temporal Self-Attention Graph Convolutional Networks for Traffic-Flow Prediction". Applied Sciences 13, n.º 11 (2 de junho de 2023): 6796. http://dx.doi.org/10.3390/app13116796.
Texto completo da fonteHuang, Xiaohui, Yuanchun Lan, Yuming Ye, Junyang Wang e Yuan Jiang. "Traffic Flow Prediction Based on Multi-Mode Spatial-Temporal Convolution of Mixed Hop Diffuse ODE". Electronics 11, n.º 19 (22 de setembro de 2022): 3012. http://dx.doi.org/10.3390/electronics11193012.
Texto completo da fonteGe, Liang, Siyu Li, Yaqian Wang, Feng Chang e Kunyan Wu. "Global Spatial-Temporal Graph Convolutional Network for Urban Traffic Speed Prediction". Applied Sciences 10, n.º 4 (22 de fevereiro de 2020): 1509. http://dx.doi.org/10.3390/app10041509.
Texto completo da fonteGoścień, Róża. "On the Efficient Flow Restoration in Spectrally-Spatially Flexible Optical Networks". Electronics 10, n.º 12 (18 de junho de 2021): 1468. http://dx.doi.org/10.3390/electronics10121468.
Texto completo da fonteJiang, Jiawei, Chengkai Han, Wayne Xin Zhao e Jingyuan Wang. "PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 4 (26 de junho de 2023): 4365–73. http://dx.doi.org/10.1609/aaai.v37i4.25556.
Texto completo da fonteBarthelemy, Marc, Bernard Gondran e Eric Guichard. "Spatial structure of the internet traffic". Physica A: Statistical Mechanics and its Applications 319 (março de 2003): 633–42. http://dx.doi.org/10.1016/s0378-4371(02)01382-1.
Texto completo da fonteDu, Wen-Bo, Xing-Lian Zhou, Zhen Chen, Kai-Quan Cai e Xian-Bin Cao. "Traffic dynamics on coupled spatial networks". Chaos, Solitons & Fractals 68 (novembro de 2014): 72–77. http://dx.doi.org/10.1016/j.chaos.2014.07.009.
Texto completo da fonteNewell, Gordon F. "Comments on spatial models of traffic". Transportation Research Part B: Methodological 27, n.º 3 (junho de 1993): 185–88. http://dx.doi.org/10.1016/0191-2615(93)90028-9.
Texto completo da fonteYALÇIN, Güler. "SPATIAL ANALYSIS OF THE TRAFFIC ACCIDENTS FOR URBAN TRAFFIC MANAGEMENT". INTERNATIONAL REFEREED JOURNAL OF ENGINEERING AND SCIENCES 2, n.º 3 (30 de abril de 2015): 1. http://dx.doi.org/10.17366/uhmfd.2015310571.
Texto completo da fonteXiao, Tianzheng, Huapu Lu, Jianyu Wang e Katrina Wang. "Predicting and Interpreting Spatial Accidents through MDLSTM". International Journal of Environmental Research and Public Health 18, n.º 4 (3 de fevereiro de 2021): 1430. http://dx.doi.org/10.3390/ijerph18041430.
Texto completo da fonteYang, Yanfang, Jiandong Cao, Yong Qin, Limin Jia, Honghui Dong e Aomuhan Zhang. "Spatial correlation analysis of urban traffic state under a perspective of community detection". International Journal of Modern Physics B 32, n.º 12 (3 de maio de 2018): 1850150. http://dx.doi.org/10.1142/s0217979218501503.
Texto completo da fonteXu, Chengcheng, Chen Wang, Wei Wang, Jie Bao e Menglin Yang. "Investigating Spatial Interdependence in E-Bike Choice Using Spatially Autoregressive Model". PROMET - Traffic&Transportation 29, n.º 4 (28 de agosto de 2017): 351–62. http://dx.doi.org/10.7307/ptt.v29i4.2144.
Texto completo da fonteGao, Min, Yingmei Wei, Yuxiang Xie e Yitong Zhang. "Traffic Prediction with Self-Supervised Learning: A Heterogeneity-Aware Model for Urban Traffic Flow Prediction Based on Self-Supervised Learning". Mathematics 12, n.º 9 (24 de abril de 2024): 1290. http://dx.doi.org/10.3390/math12091290.
Texto completo da fonteLac, C., R. P. Donnelly, V. Masson, S. Pal, S. Donier, S. Queguiner, G. Tanguy, L. Ammoura e I. Xueref-Remy. "CO<sub>2</sub> dispersion modelling over Paris region within the CO<sub>2</sub>-MEGAPARIS project". Atmospheric Chemistry and Physics Discussions 12, n.º 10 (25 de outubro de 2012): 28155–93. http://dx.doi.org/10.5194/acpd-12-28155-2012.
Texto completo da fonteYi, Ran, Yang Zhou, Xin Wang, Zhiyuan Liu, Xiaotian Li e Bin Ran. "Spatially Formulated Connected Automated Vehicle Trajectory Optimization with Infrastructure Assistance". Journal of Advanced Transportation 2022 (20 de maio de 2022): 1–15. http://dx.doi.org/10.1155/2022/6184790.
Texto completo da fonteGe, Fengjian, Wanxu Chen, Yuanyuan Zeng e Jiangfeng Li. "The Nexus between Urbanization and Traffic Accessibility in the Middle Reaches of the Yangtze River Urban Agglomerations, China". International Journal of Environmental Research and Public Health 18, n.º 7 (6 de abril de 2021): 3828. http://dx.doi.org/10.3390/ijerph18073828.
Texto completo da fonteYin, Hong Yan. "Study of Traffic Accessibility in Poyang Lake Economic Zone Oriented by High-Speed Railway". Applied Mechanics and Materials 178-181 (maio de 2012): 1778–81. http://dx.doi.org/10.4028/www.scientific.net/amm.178-181.1778.
Texto completo da fonteLian, Qingyun, Wei Sun e Wei Dong. "Hierarchical Spatial-Temporal Neural Network with Attention Mechanism for Traffic Flow Forecasting". Applied Sciences 13, n.º 17 (28 de agosto de 2023): 9729. http://dx.doi.org/10.3390/app13179729.
Texto completo da fonteJiang, Wenhao, Yunpeng Xiao, Yanbing Liu, Qilie Liu e Zheng Li. "Bi-GRCN: A Spatio-Temporal Traffic Flow Prediction Model Based on Graph Neural Network". Journal of Advanced Transportation 2022 (1 de fevereiro de 2022): 1–12. http://dx.doi.org/10.1155/2022/5221362.
Texto completo da fonteXu, Dong-wei, Yong-dong Wang, Li-min Jia, Gui-jun Zhang e Hai-feng Guo. "Compression Algorithm of Road Traffic Spatial Data Based on LZW Encoding". Journal of Advanced Transportation 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/8182690.
Texto completo da fonteZhang, Rui, Fei Xie, Jianjun Shi, Jing Zhao, Jiquan Yang e Xu Ling. "Spatial-Temporal Semantic Neural Network for Time Series Forecasting". Journal of Physics: Conference Series 2203, n.º 1 (1 de fevereiro de 2022): 012033. http://dx.doi.org/10.1088/1742-6596/2203/1/012033.
Texto completo da fonteWu, Xiaoyun, e Cynthia Lum. "The practice of proactive traffic stops". Policing: An International Journal 43, n.º 2 (26 de novembro de 2019): 229–46. http://dx.doi.org/10.1108/pijpsm-06-2019-0089.
Texto completo da fonteHan, Xing, Guowei Zhu, Ling Zhao, Ronghua Du, Yuhan Wang, Zhe Chen, Yang Liu e Silu He. "Ollivier–Ricci Curvature Based Spatio-Temporal Graph Neural Networks for Traffic Flow Forecasting". Symmetry 15, n.º 5 (27 de abril de 2023): 995. http://dx.doi.org/10.3390/sym15050995.
Texto completo da fonteZhou, Junwei, Xizhong Qin, Yuanfeng Ding e Haodong Ma. "Spatial–Temporal Dynamic Graph Differential Equation Network for Traffic Flow Forecasting". Mathematics 11, n.º 13 (26 de junho de 2023): 2867. http://dx.doi.org/10.3390/math11132867.
Texto completo da fonteIštoka Otković, Irena, Barbara Karleuša, Aleksandra Deluka-Tibljaš, Sanja Šurdonja e Mario Marušić. "Combining Traffic Microsimulation Modeling and Multi-Criteria Analysis for Sustainable Spatial-Traffic Planning". Land 10, n.º 7 (24 de junho de 2021): 666. http://dx.doi.org/10.3390/land10070666.
Texto completo da fonteYu, Hongru, Shejun Deng, Caoye Lu, Yucheng Tang, Shijun Yu, Lu Liu e Tao Ji. "Research on the Evolution Mechanism of Congestion in the Entrances and Exits of Parking Facilities Based on the Improved Spatial Autoregressive Model". Journal of Advanced Transportation 2021 (29 de agosto de 2021): 1–15. http://dx.doi.org/10.1155/2021/8380247.
Texto completo da fonteLi, Y., Q. Zhao e M. Wang. "ANALYSIS THE INFLUENCING FACTORS OF URBAN TRAFFIC FLOWS BY USING NEW AND EMERGING URBAN BIG DATA AND DEEP LEARNING". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2022 (2 de junho de 2022): 537–43. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2022-537-2022.
Texto completo da fonteZhou, Shaobo, Xiaodong Zang, Junheng Yang, Wanying Chen, Jiahao Li e Shuyi Chen. "Modelling the Coupling Relationship between Urban Road Spatial Structure and Traffic Flow". Sustainability 15, n.º 14 (17 de julho de 2023): 11142. http://dx.doi.org/10.3390/su151411142.
Texto completo da fonteChen, Renyi, e Huaxiong Yao. "Hybrid Graph Models for Traffic Prediction". Applied Sciences 13, n.º 15 (27 de julho de 2023): 8673. http://dx.doi.org/10.3390/app13158673.
Texto completo da fonteZhang, Xiao Na, Ming Yao, Feng Zhu e Jie Ni. "Traffic Image Segmentation Based on Gaussian Mixture Model with Spatial Information and Sampling". Applied Mechanics and Materials 380-384 (agosto de 2013): 3702–5. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3702.
Texto completo da fonteZeng, Hui, Chaojie Jiang, Yuanchun Lan, Xiaohui Huang, Junyang Wang e Xinhua Yuan. "Long Short-Term Fusion Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting". Electronics 12, n.º 1 (3 de janeiro de 2023): 238. http://dx.doi.org/10.3390/electronics12010238.
Texto completo da fonteWang, Beibei, Youfang Lin, Shengnan Guo e Huaiyu Wan. "GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 5 (18 de maio de 2021): 4402–9. http://dx.doi.org/10.1609/aaai.v35i5.16566.
Texto completo da fonteCui, Jiaxing, Ruihao Li, Lingyu Zhang e Ying Jing. "Spatially Illustrating Leisure Agriculture: Empirical Evidence from Picking Orchards in China". Land 10, n.º 6 (13 de junho de 2021): 631. http://dx.doi.org/10.3390/land10060631.
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