Machine learning for transportation research and applications / Yinhai Wang, Smart Transportation Applications and Research Laboratory, Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States, Zhiyong Cui, School of Transportation Science and Engineering, Beihang University, Beijing, China, Ruimin Ke, Department of Civil Engineering, University of Texas, El Paso, El Paso, TX, United States.
| Author/creator | Wang, Yinhai |
| Other author | Cui, Zhiyong, 1989- |
| Other author | Ke, Ruimin. |
| Format | Electronic |
| Publication Info | Amsterdam, Netherlands : Elsevier, [2023] |
| Description | xi, 239 pages : illustrations (some color) ; 23 cm |
| Supplemental Content | Full text available from Elsevier ScienceDirect eBook - Social Sciences 2023 |
| Subjects |
| Abstract | "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."-- Page 4 of cover |
| Bibliography note | Includes bibliographical references (pages 217-229) and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Issued in other form | Ebook version: Wang, Yinhai. Machine learning for transportation research and applications. Amsterdam, Netherlands : Elsevier, [2023] 9780323996808 |
| Genre/form | Electronic books. |
| LCCN | 2023279979 |
| ISBN | 9780323961264 (paperback) |
| ISBN | 0323961266 (paperback) |
| ISBN | (eBook) |
| ISBN | (eBook) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |