M. Akhtar, S. MoridpourA review of traffic congestion prediction using artificial intelligence J. Adv. Transp., 2021 (2021), p. 18,10.1155/2021/8878011 Article ID 8878011pages Google Scholar [39] E. Mangina, P.I. VlachosThe changing role of information technology in food and beverage logis...
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Source:Architecture of the traffic prediction system Model Validation The model was validated using data from almost 7,500 kilometres of urban areas in Boston, Los Angeles, Chicago, and New York City. Additionally, theresearchmakes use of 4.2 million records from theUS Accidents dataset. Each...
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In addition to moving forward and backward in time, the application of the new framework allows us to locate future traffic jams (congestions). This paper reviews the evolution of the existing traffic prediction's approaches and the edge given by AI to make the best decisions; we will focus...
3 Simpler is better Multilevel Abstraction with Graph Convolutional Recurrent Neural Network Cells for Traffic Prediction 标题:越简单越好:使用图卷积递归神经网络单元进行交通预测的多级抽象 文章链接:https://arxiv.org/abs/2209.03858 摘要:近年来,图形神经网络(GNN)与递归神经网络(RNN)的变体相结合,在时空预测...
Implementation and Knowledge Graphs of the ICCV 2023 workshop paper "nuScenes Knowledge Graph - A comprehensive semantic representation of traffic scenes for trajectory prediction" bcaipaper-resource UpdatedJul 1, 2024 boschresearch/sofc-exp_textmining_resources ...
An online prediction and imputation framework for spatiotemporal traffic status We propose a framework based on the aforementioned LSTM-(GL-)ReMF/TF models which is able to make spatiotemporal predictions using raw incomplete data and perform online data imputation simultaneously. As shown in the figu...
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5 ways machine learning is used in cybersecurity: To classify data - Machine learning algorithms can classify data into different categories based on learned patterns. In cybersecurity, this helps in categorizing types of network traffic, identifying whether data is normal or malicious, and distinguis...