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Titlebook: Intelligent Transport Systems, From Research and Development to the Market Uptake; 4th EAI Internationa Ana Lúcia Martins,João C. Ferreira,

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书目名称Intelligent Transport Systems, From Research and Development to the Market Uptake
副标题4th EAI Internationa
编辑Ana Lúcia Martins,João C. Ferreira,Vera Costa
视频videohttp://file.papertrans.cn/471/470144/470144.mp4
丛书名称Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engi
图书封面Titlebook: Intelligent Transport Systems, From Research and Development to the Market Uptake; 4th EAI Internationa Ana Lúcia Martins,João C. Ferreira,
描述This book constitutes the proceedings of the 4.th. International Conference on Intelligent Transport Systems, INTSYS 2020, which was held in December 2020. Due to COVID-19 pandemic the conference was held virtually. . With the globalization of trade and transportation and the consequent multi-modal solutions used, additional challenges are faced by organizations and countries. Intelligent Transport Systems make transport safer, more efficient, and more sustainable by applying information and communication technologies to all transportation modes. The 16 revised full papers in this book were selected from 38 submissions and are organized in three thematic sessions on mobility; applications; simulation and prediction..
出版日期Conference proceedings 2021
关键词applied computing; artificial intelligence; bandwidth; communication systems; computer networks; data com
版次1
doihttps://doi.org/10.1007/978-3-030-71454-3
isbn_softcover978-3-030-71453-6
isbn_ebook978-3-030-71454-3Series ISSN 1867-8211 Series E-ISSN 1867-822X
issn_series 1867-8211
copyrightICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2021
The information of publication is updating

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Performance Evaluation of Object Detection Algorithms Under Adverse Weather Conditions normal and foggy environmental conditions. It is shown that the detection performance deteriorates considerably when exposed to fog. Further, the results suggest that some algorithms are more robust towards fog than others.
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EMD-SVR: A Hybrid Machine Learning Method to Improve the Forecasting Accuracy of Highway Tollgates Tort Vector Regression (EMD-SVR). Results claim that compared with SVR, the new proposed hybrid prediction model, EMD-SVR, can effectively improve prediction accuracy. Better forecasting of the traffic load will provide safer roads but will also lower the carbon emissions caused by longer traveling times.
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