Can I read Machine Learning for Transportation Research and Applications on EtoBox?

Machine Learning for Transportation Research and Applications by Yinhai Wang, Zhiyong Cui, Ruimin Ke is a nonfiction available to read on EtoBox.

What is Machine Learning for Transportation Research and Applications about?

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 (ML). 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. Designing and applying proper Machine Learning algorithms to problems of different domains, including transportation problems, require a comprehensive understanding of every corner of machine learning techniques and basic theories. The Chapter 2 introduces a spectrum of key concepts in the field of Machine Learning, starting with the definition and categories of Machine Learning, and then covering the basic building block

Who reads Machine Learning for Transportation Research and Applications?

Author

Yinhai Wang, Zhiyong Cui, Ruimin Ke

Publisher

Elsevier Science & Technology

Published

2023

Language

EN

ISBN

9780323961264

Category

nonfiction

Subjects

Psychology, Science, Economics