205,69 €
241,99 €
-15% su kodu: ENG15
Data-Driven Solutions to Transportation Problems
Data-Driven Solutions to Transportation Problems
205,69 €
241,99 €
  • Išsiųsime per 12–18 d.d.
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 c…
  • Leidėjas:
  • ISBN-10: 0128170263
  • ISBN-13: 9780128170267
  • Formatas: 15.2 x 22.9 x 1.6 cm, minkšti viršeliai
  • Kalba: Anglų
  • Extra -15 % nuolaida šiai knygai su kodu: ENG15

Data-Driven Solutions to Transportation Problems (el. knyga) (skaityta knyga) | knygos.lt

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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 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.

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205,69 €
241,99 €
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  • Autorius: Yinhai Wang
  • Leidėjas:
  • ISBN-10: 0128170263
  • ISBN-13: 9780128170267
  • Formatas: 15.2 x 22.9 x 1.6 cm, minkšti viršeliai
  • Kalba: Anglų Anglų

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.

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