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Logic-Driven Traffic Big Data Analytics
Logic-Driven Traffic Big Data Analytics
Knygos.lt klubas Knygos.lt nariams
257,80 €
-15%
Įprastai
303,29 €
  • Išsiųsime per 12–18 d.d.
This book starts from the relationship between urban built environment and travel behavior and focuses on analyzing the origin of traffic phenomena behind the data through multi-source traffic big data, which makes the book unique and different from the previous data-driven traffic big data analysis literature. This book focuses on understanding, estimating, predicting, and optimizing mobility patterns. Readers can find multi-source traffic big data processing methods, related statistical analy…
  • Leidėjas:
  • ISBN-10: 9811680159
  • ISBN-13: 9789811680151
  • Formatas: 15.6 x 23.4 x 1.8 cm, kieti viršeliai
  • Kalba: Anglų

Logic-Driven Traffic Big Data Analytics (el. knyga) (skaityta knyga) | knygos.lt

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This book starts from the relationship between urban built environment and travel behavior and focuses on analyzing the origin of traffic phenomena behind the data through multi-source traffic big data, which makes the book unique and different from the previous data-driven traffic big data analysis literature. This book focuses on understanding, estimating, predicting, and optimizing mobility patterns. Readers can find multi-source traffic big data processing methods, related statistical analysis models, and practical case applications from this book.

This book bridges the gap between traffic big data, statistical analysis models, and mobility pattern analysis with a systematic investigation of traffic big data's impact on mobility patterns and urban planning.


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  • Autorius: Shaopeng Zhong
  • Leidėjas:
  • ISBN-10: 9811680159
  • ISBN-13: 9789811680151
  • Formatas: 15.6 x 23.4 x 1.8 cm, kieti viršeliai
  • Kalba: Anglų

This book starts from the relationship between urban built environment and travel behavior and focuses on analyzing the origin of traffic phenomena behind the data through multi-source traffic big data, which makes the book unique and different from the previous data-driven traffic big data analysis literature. This book focuses on understanding, estimating, predicting, and optimizing mobility patterns. Readers can find multi-source traffic big data processing methods, related statistical analysis models, and practical case applications from this book.

This book bridges the gap between traffic big data, statistical analysis models, and mobility pattern analysis with a systematic investigation of traffic big data's impact on mobility patterns and urban planning.


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