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Titlebook: Mobility Data-Driven Urban Traffic Monitoring; Zhidan Liu,Kaishun Wu Book 2021 The Author(s), under exclusive license to Springer Nature S

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發(fā)表于 2025-3-21 16:13:04 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Mobility Data-Driven Urban Traffic Monitoring
編輯Zhidan Liu,Kaishun Wu
視頻videohttp://file.papertrans.cn/636/635597/635597.mp4
概述Elaborates the basic workflow of mobility data-based urban traffic monitoring.Discusses future research directions on mobility data-driven traffic analysis.Solves real-world traffic problems with emer
叢書(shū)名稱SpringerBriefs in Computer Science
圖書(shū)封面Titlebook: Mobility Data-Driven Urban Traffic Monitoring;  Zhidan Liu,Kaishun Wu Book 2021 The Author(s), under exclusive license to Springer Nature S
描述.This book introduces the concepts of mobility data and data-driven urban traffic monitoring. A typical framework of mobility data-based urban traffic monitoring is also presented, and it describes the processes of mobility data collection, data processing, traffic modelling, and some practical issues of applying the models for urban traffic monitoring...This book presents three novel mobility data-driven urban traffic monitoring approaches. First, to attack the challenge of mobility data sparsity, the authors propose a compressive sensing-based urban traffic monitoring approach. This solution mines the traffic correlation at the road network scale and exploits the compressive sensing theory to recover traffic conditions of the whole road network from sparse traffic samplings. Second, the authors have compared the traffic estimation performances between linear and nonlinear traffic correlation models and proposed a dynamical? non-linear traffic correlation modelling-basedurban traffic monitoring approach. To address the challenge of involved huge computation overheads, the approach adapts the traffic modelling and estimations tasks to Apache Spark, a popular parallel computing fram
出版日期Book 2021
關(guān)鍵詞Urban traffic monitoring; Mobility data; Intelligent Transportation System; Traffic modelling; Compress
版次1
doihttps://doi.org/10.1007/978-981-16-2241-0
isbn_softcover978-981-16-2240-3
isbn_ebook978-981-16-2241-0Series ISSN 2191-5768 Series E-ISSN 2191-5776
issn_series 2191-5768
copyrightThe Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
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2191-5768 raffic analysis.Solves real-world traffic problems with emer.This book introduces the concepts of mobility data and data-driven urban traffic monitoring. A typical framework of mobility data-based urban traffic monitoring is also presented, and it describes the processes of mobility data collection,
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https://doi.org/10.1007/978-981-16-2241-0Urban traffic monitoring; Mobility data; Intelligent Transportation System; Traffic modelling; Compress
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,Preventive Geriatrics—A Way Towards Active Ageing,venting or delaying diseases in elderly age group. The priority for preventive measures should begin before the onset of diseases and or in preventing or delaying the complications of the existing chronic diseases. The preventive strategies will include modifiable, protective and screening measures.
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