Data-Driven Solutions to Transportation Problems - Yinhai Wang,Ziqiang Zeng
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Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in trans ... Pilns apraksts
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Aprašymas
Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more.
Vairāk informācijas
| Autors | Yinhai Wang, Ziqiang Zeng |
|---|---|
| Izdevējs | Elsevier Science |
| Izlaides gads | 2018 |
| Vāka tips | Mīkstais vāks |
| EAN | 9780128170267 |