Machine Learning For Transportation Research And Applications

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.

• | Author: Yinhai Wang, Zhiyong Cui, Ruimin Ke
• | Publisher: Elsevier
• | Publication Date: Apr 25, 2023
• | Number of Pages: 252 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 0323961266
• | ISBN-13: 9780323961264