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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Technik Bau- und Umwelttechnik Data Science for Maritime Transportation
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Beschreibung
This book provides a comprehensive and application-oriented introduction to data science, machine learning, and deep learning methods for maritime transportation. It is written to help readers understand how maritime data can be processed, analyzed, modeled, and used to support digitalization for shipping industry. The book is organized into two parts. Part I, Fundamentals and Concepts, introduces… the theoretical and methodological foundations required for maritime data science. It begins with maritime transportation data sources, structures, and characteristics, followed by essential data preprocessing techniques. It then presents methods for vessel trajectory representation, transformation, and analysis. The part also introduces the fundamental concepts of machine learning and deep learning, with a focus on their relevance to maritime applications. The final chapter of this part provides background knowledge on vessel maneuvering behavior and motion dynamics, establishing a bridge between physical understanding and data-driven modeling. Part II, Practical Applications and Case Studies, focuses on representative real-world problems in maritime data science and intelligent shipping. It covers trajectory clustering and pattern mining, deep learning-based vessel trajectory forecasting, anomaly detection using reconstruction methods, data-driven and physics-informed modeling of vessel propulsion power, regional ocean wave prediction, maritime traffic flow forecasting using graph neural networks, and vessel estimated time of arrival (ETA) prediction using machine learning. Each application chapter is designed as a self-contained case study that combines problem formulation, modeling methodology, implementation details, and practical interpretation. The book is suitable for graduate students, researchers, and practitioners in academia and industry. It can be used both as a structured textbook and as a practical reference for self-study. With hands-on Python examples and source code provided through the author’s GitHub repository, the book enables readers to reproduce key methods, understand maritime data characteristics, select appropriate modeling approaches, and develop data-driven solutions for real operational scenarios in maritime transportation. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
17.11.2026
Sprache
Englisch
EAN
9789819250417
Herausgeber
Springer Singapore
Sonderedition
Nein
Autor
Liang Zhao
Seitenanzahl
440
Einbandart
Gebundene Ausgabe
Schlagwörter
Logistics, Maritime Transportation, Deep learning, Port management, Data science, Artificial Intelligence, Maritime shipping
Thema-Inhalt
TNH - Verkehrsingenieurwesen, Verkehrsplanung
TRL - Schiffbau und Schifffahrtswesen
Höhe
235 mm
Breite
15.5 cm
Transparenz & Sicherheit
Hersteller: Springer Nature Customer Service Center GmbH, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com
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