257,03 €
302,39 €
-15% su kodu: ENG15
Machine Learning for Transportation Research and Applications
Machine Learning for Transportation Research and Applications
257,03
302,39 €
  • Išsiųsime per 12–18 d.d.
Transportation issues are often too complicated to be addressed by conventional parametric methods. Increasing data availability and recent advancements in machine learning provide new methods to tackle the challenging transportation problems. Readers will learn how to develop and apply different types of machine learning models to transportation related problems. Example applications include transportation data generations, traffic sensing, transportation mode recognition, transportation syste…
  • Leidėjas:
  • ISBN-10: 0323961266
  • ISBN-13: 9780323961264
  • Formatas: 15.2 x 22.9 x 1.4 cm, minkšti viršeliai
  • Kalba: Anglų
  • Extra -15 % nuolaida šiai knygai su kodu: ENG15

Machine Learning for Transportation Research and Applications (el. knyga) (skaityta knyga) | knygos.lt

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Transportation issues are often too complicated to be addressed by conventional parametric methods. Increasing data availability and recent advancements in machine learning provide new methods to tackle the challenging transportation problems. Readers will learn how to develop and apply different types of machine learning models to transportation related problems. Example applications include transportation data generations, traffic sensing, transportation mode recognition, transportation system management and control, traffic flow prediction, and traffic safety analysis.

EXTRA 15 % nuolaida su kodu: ENG15

257,03
302,39 €
Išsiųsime per 12–18 d.d.

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  • Autorius: Yinhai Wang
  • Leidėjas:
  • ISBN-10: 0323961266
  • ISBN-13: 9780323961264
  • Formatas: 15.2 x 22.9 x 1.4 cm, minkšti viršeliai
  • Kalba: Anglų Anglų

Transportation issues are often too complicated to be addressed by conventional parametric methods. Increasing data availability and recent advancements in machine learning provide new methods to tackle the challenging transportation problems. Readers will learn how to develop and apply different types of machine learning models to transportation related problems. Example applications include transportation data generations, traffic sensing, transportation mode recognition, transportation system management and control, traffic flow prediction, and traffic safety analysis.

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