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|a Data Analytics: Paving the Way to Sustainable Urban Mobility
|h [electronic resource] :
|b Proceedings of 4th Conference on Sustainable Urban Mobility (CSUM2018), 24 - 25 May, Skiathos Island, Greece /
|c edited by Eftihia G. Nathanail, Ioannis D. Karakikes.
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| 250 |
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|a 1st ed. 2019.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2019.
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| 300 |
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|a XIX, 868 p. 235 illus., 199 illus. in color.
|b online resource.
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|a text
|b txt
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|a Advances in Intelligent Systems and Computing,
|x 2194-5357 ;
|v 879
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| 505 |
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|a Have information technologies forgotten pedestrians? to what extent can it/its improve pedestrian's mobility and safety -- Trip generation rates for a University campus: the case of the Aristotle University of Thessaloniki, Greece -- An analysis on drivers' self-reported questionnaire responses, regarding aggressive driving, attitude toward cyclists and personal values -- Redesigning the seafront area of Paphos -- Development of an aggregate indicator for evaluating sustainable urban mobility in the city of Xanthi, Greece -- Performance evaluation of GLOSA-algorithms under realistic traffic conditions using C2I-communication -- Measuring the spatial accessibility of public transport: the case of the new urban rail systems in the city of Thessaloniki, Greece.
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| 520 |
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|a This book aims at showing how big data sources and data analytics can play an important role in sustainable mobility. It is especially intended to provide academicians, researchers, practitioners and decision makers with a snapshot of methods that can be effectively used to improve urban mobility. The different chapters, which report on contributions presented at the 4th Conference on Sustainable Urban Mobility, held on May 24-25, 2018, in Skiathos Island, Greece, cover different thematic areas, such as social networks and traveler behavior, applications of big data technologies in transportation and analytics, transport infrastructure and traffic management, transportation modeling, vehicle emissions and environmental impacts, public transport and demand responsive systems, intermodal interchanges, smart city logistics systems, data security and associated legal aspects. They show in particular how to apply big data in improving urban mobility, discuss important challenges in developing and implementing analytics methods and provide the reader with an up-to-date review of the most representative research on data management techniques for enabling sustainable urban mobility .
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|a Transportation engineering.
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|a Traffic engineering.
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|a Data mining.
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| 650 |
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|a Sustainable development.
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| 650 |
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|a Energy policy.
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| 650 |
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|a Energy and state.
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|a Transportation Technology and Traffic Engineering.
|0 http://scigraph.springernature.com/things/product-market-codes/T23120
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| 650 |
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|a Data Mining and Knowledge Discovery.
|0 http://scigraph.springernature.com/things/product-market-codes/I18030
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| 650 |
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|a Sustainable Development.
|0 http://scigraph.springernature.com/things/product-market-codes/U34000
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| 650 |
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|a Energy Policy, Economics and Management.
|0 http://scigraph.springernature.com/things/product-market-codes/112000
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1 |
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|a Nathanail, Eftihia G.
|e editor.
|4 edt
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| 700 |
1 |
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|a Karakikes, Ioannis D.
|e editor.
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|4 http://id.loc.gov/vocabulary/relators/edt
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|i Printed edition:
|z 9783030023041
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|i Printed edition:
|z 9783030023065
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| 830 |
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|a Advances in Intelligent Systems and Computing,
|x 2194-5357 ;
|v 879
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-030-02305-8
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
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