Road Traffic Modeling and Management
Using Statistical Monitoring and Deep Learning
Road Traffic Modeling and Management: Using Statistical Monitoring and Deep Learning provides a framework for understanding and enhancing road traffic monitoring and management. The book examines commonly used traffic analysis methodologies as well the emerging methods that use deep learning methods. Other sections discuss how to understand statistical models and machine learning algorithms and how to apply them to traffic modeling, estimation, forecasting and traffic congestion monitoring. Providing both a theoretical framework along with practical technical solutions, this book is ideal for researchers and practitioners who want to improve…
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Produktdetails
Weitere Autoren: Zeroual, Abdelhafid (Associate Researcher, University of Guelma, Guelma, Algeria) / Hittawe, Mohamad Mazen (Research Scientist, King Abdullah University of Science and Technology, Saudi Arabia) / Sun, Ying (King Abdullah University of Science and Technology, Saudi Arabia)
- ISBN: 978-0-12-823432-7
- EAN: 9780128234327
- Produktnummer: 36810023
- Verlag: Elsevier Science Publishing Co Inc
- Sprache: Englisch
- Erscheinungsjahr: 2021
- Seitenangabe: 268 S.
- Masse: H15.2 cm x B22.9 cm x D1.9 cm 440 g
- Gewicht: 440
- Sonstiges: Professional & Vocational
Über den Autor
Fouzi Harrou received the M.Sc. degree in telecommunications and networking from the University of Paris VI, France, and the Ph.D. degree in systems optimization and security from the University of Technology of Troyes (UTT), France. He was an Assistant Professor with UTT for one year and with the Institute of Automotive and Transport Engineering, Nevers, France, for one year. He was also a Postdoctoral Research Associate with the Systems Modeling and Dependability Laboratory, UTT, for one year. He was a Research Scientist with the Chemical Engineering Department, Texas A&M University at Qatar, Doha, Qatar, for three years. He is actually a Research Scientist with the Division of Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science and Technology. He is the author of more than 150 refereed journals and conference publications and book chapters. He is co-author of the book Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches: Theory and Practical Applications (Elsevier, 2020). Dr. Harrou's research interests are in the area of statistical anomaly detection and process monitoring with a particular emphasis on data-driven, machine learning/deep learning methods. The algorithms developed in Dr. Harrou's research are utilized in many applications to improve the operation of various environmental, chemical, and electrical systems.
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