Ship As Wave Buoy: Data-Driven Sea State Estimation Based on Ship Motion Data
Year: 2026 Language: English Author: Xu Cheng and Others Genre: Research papers, Textbooks Publisher: Springer Edition: 1st ISBN: 9789819567423 Format: PDF Quality: eBook Pages count: 237 Description: This monograph addresses a central problem in contemporary ocean engineering and maritime operations: how to obtain reliable, real-time sea state information from the motion responses of ships themselves. Rather than relying only on sparse and costly instruments such as dedicated wave buoys, X-band wave radars, or satellites, we embrace the “ship-as-a-buoy” paradigm and develop a suite of deep learning (DL) methods that convert routine multivariate motion measurements into accurate and operationally useful sea state estimates. This book is intended for researchers, graduate students, and advanced practi-tioners in ocean engineering and naval architecture, marine operations and maritime autonomy, as well as for those in machine learning, particularly time-series modeling and deep learning. A basic familiarity with linear systems, probability and statistics, and introductory deep learning will be helpful, but each chapter is designed to be as self-contained as possible.
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Ship As Wave Buoy: Data-Driven Sea State Estimation Based on Ship Motion Data
Language: English
Author: Xu Cheng and Others
Genre: Research papers, Textbooks
Publisher: Springer
Edition: 1st
ISBN: 9789819567423
Format: PDF
Quality: eBook
Pages count: 237
Description: This monograph addresses a central problem in contemporary ocean engineering and maritime operations: how to obtain reliable, real-time sea state information from the motion responses of ships themselves. Rather than relying only on sparse and costly instruments such as dedicated wave buoys, X-band wave radars, or satellites, we embrace the “ship-as-a-buoy” paradigm and develop a suite of deep learning (DL) methods that convert routine multivariate motion measurements into accurate and operationally useful sea state estimates.
This book is intended for researchers, graduate students, and advanced practi-tioners in ocean engineering and naval architecture, marine operations and maritime autonomy, as well as for those in machine learning, particularly time-series modeling and deep learning. A basic familiarity with linear systems, probability and statistics, and introductory deep learning will be helpful, but each chapter is designed to be as self-contained as possible.
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