Logic-driven traffic big data analytics : methodology and applications for planning / Shaopeng Zhong, Daniel (Jian) Sun.

Unlimited

Authorized users

Can lend chapters, not whole ebooks

Logic-driven traffic big data analytics : methodology and applications for planning / Shaopeng Zhong, Daniel (Jian) Sun.

9789811680168 (electronic bk.)
9811680167 (electronic bk.)
9789811680151
9811680159

Singapore : Springer, [2022]

©2022

English

1 online resource : illustrations (chiefly color)

10.1007/978-981-16-8016-8 doi

HE336.A8 Z56 2022

388.3/14

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 datas impact on mobility patterns and urban planning.

Includes index.

Access limited to authorized users.

Print version: 9789811680151

Online Resources > Ebooks
All Resources