Machine learning for transportation research and applications /

Transportation is a combination of systems that presents a variety of challenges often too intricate to be addressed by conventional parametric methods. Increasing data availability and recent advancements in machine learning provide new methods to tackle challenging transportation problems. This te...

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Bibliographic Details
Main Authors: Wang, Yinhai (Author), Cui, Zhiyong, 1989- (Author), Ke, Ruimin (Author)
Corporate Author: ScienceDirect (Online service)
Format: eBook
Language:English
Published: Amsterdam : Elsevier, 2023.
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:Transportation is a combination of systems that presents a variety of challenges often too intricate to be addressed by conventional parametric methods. Increasing data availability and recent advancements in machine learning provide new methods to tackle challenging transportation problems. This textbook is designed for college or graduate-level students in transportation or closely related fields to study and understand fundamentals in machine learning. Readers will learn how to develop and apply various types of machine learning models to transportation-related problems. Example applications include traffic sensing, data-quality control, traffic prediction, transportation asset management, traffic-system control and operations, and traffic-safety analysis.
Physical Description:1 online resource
ISBN:0323996809
9780323996808