E-Book, Englisch, 275 Seiten
Liu / Gu Transportation Big Data
1. Auflage 2024
ISBN: 978-0-443-33892-2
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark
Theory and Methods
E-Book, Englisch, 275 Seiten
ISBN: 978-0-443-33892-2
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark
Transportation Big Data: Theory and Methods is centered on the big data theory and methods. Big data is now a key topic in transportation, simply because the volume of data has increased exponentially due to the growth in the amount of traffic (all modes) and detectors. This book provides a structured analysis of the commonly used methods for handling transportation big data; it is supported by a wealth of transportation engineering examples, together with codes. It offers a concise, yet comprehensive, description of the key techniques and important tools in transportation big data analysis. - Covers big data applications in transportation engineering in real-world scenarios - Shows how to select different machine learning algorithms for processing, analyzing, and modeling transportation data - Provides an overview of the fundamental concepts of machine learning and how classical algorithms can be applied to transportation-related problems - Provides an overview of Python's basic syntax and commonly used modules, enabling practical data analysis and modeling tasks using Python
Dr. Zhiyuan (Terry) Liu is a Professor at the School of Transportation at Southeast University, China. He obtained his PhD degree from the National University of Singapore, Singapore. His research interests lie in the intersection and integration of transportation system analysis, big data analytics, and machine learning methods. He has published more than 100 papers in these areas.
