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This book explores the principles of analysing maritime-transportation related practical problems using data-driven models, with a particular focus on machine learning. Coverage includes data-enabled methodologies, technologies, applications and case studies.
A propos de l'auteur
Ran Yan is a research assistant professor in the Department of Logistics and Maritime Studies at The Hong Kong Polytechnic University (PolyU), China. Dr. Yan received her Bachelor of Science degree from Hohai University in China in 2018 and her Master of Philosophy and Doctor of Philosophy degrees from The Hong Kong Polytechnic University in 2020 and 2022, respectively. Dr. Yan's research interests include applying data analytics methods and technologies to improve shipping efficiency and green shipping management. Dr. Yan has published more than 30 papers in international journals and conference proceedings, such as
Transportation Research Part B/C/E,
Transport Policy,
Journal of Computational Science,
Maritime Policy & Management,
Ocean Engineering,
Engineering,
Sustainability, and
Electronic Research Archive, and won several times of best paper/student paper award from international conferences. Dr. Yan is an editorial assistant of
Cleaner Logistics and Supply Chain.
Résumé
This book explores the principles of analysing maritime-transportation related practical problems using data-driven models, with a particular focus on machine learning. Coverage includes data-enabled methodologies, technologies, applications and case studies.
