
Transportation Big Data
Theory and Methods
Elsevier (Publisher)
Published on 5. December 2024
Book
Paperback/Softback
454 pages
978-0-443-33891-5 (ISBN)
Description
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.
More details
Language
English
Place of publication
Philadelphia
United States
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 227 mm
Width: 150 mm
Thickness: 24 mm
Weight
722 gr
ISBN-13
978-0-443-33891-5 (9780443338915)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

E-Book
11/2024
Elsevier
€126.99
Available for download
Persons
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. Dr. Ziyuan (Frank) Gu is an Associate Professor at the School of Transportation at Southeast University, China. He obtained his PhD degree from the University of New South Wales Sydney, Australia. His research interests include data-driven transportation system analysis and machine learning-assisted traffic simulation and optimization. He has published over 40 papers in these areas. Dr. Pan Liu is a Professor at the School of Transportation at Southeast University, China. He obtained his PhD degree from the University of South Florida, Tampa, USA. He has authored or co-authored over 100 papers in prestigious transportation journals. His research interests include transportation big data analysis, traffic operations and safety, and intelligent transportation systems
Author
Professor, Southeast University, China
School of Transportation, Southeast University, China
Southeast University
Content
1. Introduction
2. Data analysis in Python
3.Data preprocessing and exploratory data analysis
4. Data visualization
5. Machine learning basics
6. Linear model
7. Support vector machine
8. Decision tree
9. Clustering analysis
10. Ensemble learning
11. Artificial neural network
12. Deep learning
2. Data analysis in Python
3.Data preprocessing and exploratory data analysis
4. Data visualization
5. Machine learning basics
6. Linear model
7. Support vector machine
8. Decision tree
9. Clustering analysis
10. Ensemble learning
11. Artificial neural network
12. Deep learning