Ship as Wave Buoy: Data-Driven Sea State Estimation Based on Ship Motion Data
暫譯: 作為波浮標的船舶：基於船舶運動數據的數據驅動海況估計
Cheng, Xu, Liu, Mengna, Shi, Fan
- 出版商: Springer
- 出版日期: 2026-05-08
- 售價: $8,420
- 貴賓價: 9.5 折 $7,999
- 語言: 英文
- 頁數: 225
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 9819567416
- ISBN-13: 9789819567416
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相關分類:
DeepLearning
海外代購書籍(需單獨結帳)
相關主題
商品描述
This book focuses on a comprehensive investigation into data-driven Sea State Estimation (SSE) by leveraging a vessel's own motion data. It presents a collection of advanced deep learning frameworks designed to overcome critical, real-world challenges inherent in this approach. This book systematically introduces key issues including: the class imbalance of sea state data, where rare but hazardous conditions are difficult to predict; the need for model transferability between different ships and loading conditions; and the crucial demand for security and robustness against adversarial data attacks. To solve these problems, the book introduces a suite of innovative architectures employing techniques such as densely connected convolutional networks, prototype-based classifiers, multi-scale feature learning, adversarial transfer learning, and dynamic graph networks. The efficacy of these models is rigorously validated on both public benchmarks and specialized ship motion datasets, demonstrating superior performance over existing state-of-the-art methods and providing a robust toolkit for enhancing maritime safety and efficiency.
商品描述(中文翻譯)
本書專注於透過利用船舶自身的運動數據，對數據驅動的海況估計（Sea State Estimation, SSE）進行全面調查。它呈現了一系列先進的深度學習框架，旨在克服此方法固有的關鍵現實挑戰。本書系統地介紹了幾個關鍵問題，包括：海況數據的類別不平衡，稀有但危險的條件難以預測；不同船舶和載重條件之間模型可轉移性的需求；以及對抗數據攻擊的安全性和穩健性的重要需求。為了解決這些問題，本書介紹了一套創新的架構，採用了密集連接的卷積網絡、基於原型的分類器、多尺度特徵學習、對抗性轉移學習和動態圖網絡等技術。這些模型的有效性在公共基準和專門的船舶運動數據集上進行了嚴格驗證，顯示出優於現有最先進方法的卓越性能，並提供了一個強大的工具包，以增強海事安全和效率。
作者簡介
Xu Cheng (Senior Member, IEEE) received his Ph.D. degree in Engineering from the Department of Ocean Operations and Civil Engineering, Intelligent Systems Laboratory, Norwegian University of Science and Technology (NTNU), Ålesund, Norway, in June 2020. From June 2020 to March 2022, he worked as a postdoctoral fellow, and researcher at the Department of Manufacturing and Civil Engineering, Gjøvik, Norway. From April 2022, he worked at Smart Innovation Norway as a permanent researcher. He has applied for and coordinated more than 5 projects supported by the Norwegian Research Council (NFR), the EU, and industry. He has published more than 130 papers as first and co-author and 1 book in Springer as first author in his research interests, including data analysis and artificial intelligence in maritime operations, time series analysis, and predictive maintenance of wind turbines.
Mengna Liu is a Ph.D. candidate at the School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China, in 2023. With four years of experience as an algorithm engineer, she has developed expertise in designing algorithms and optimizing data processes. Her research interests include time series modeling and data mining.
Fan Shi (Member, IEEE) is a professor at the School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China. Dr. Shi received his Ph.D. degree from Nankai University, Tianjin, China, in 2012. From June 2018 to August 2019, he was a research scholar in West Virginia University. His research interests include machine vision, pattern recognition and optics.
Xiufeng Liu received the Ph.D. degree in computer science from Aalborg University, Denmark, in 2012. He was a postdoctoral researcher at the University of Waterloo and a research scientist at IBM, Canada, from 2013 to 2014. He is currently a senior researcher at the Department of Technology, Management and Economics at the Technical University of Denmark. His research interests include smart meter data analysis, data warehousing, energy informatics, and big data.
Houxiang Zhang (Senior Member, IEEE) received the Ph.D. degree in mechanical and electronic engineering and the Habilitation degree in informatics from the University of Hamburg, Hamburg, Germany, in 2003 and February 2011, respectively. He is currently a full professor with the Department of Ocean Operations and Civil Engineering, Faculty of Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway. Since 2004, he has been a postdoctoral fellow and a Senior Researcher with the Department of Informatics, Faculty of Mathematics, Informatics and Natural Sciences, Institute of Technical Aspects of Multimodal Systems, University of Hamburg, Hamburg, Germany. He was with NTNU, where he is currently a professor of Mechatronics in April 2011. From 2011 to 2016, he also hold a Norwegian National GIFT Professorship on product and system design funded by the Norwegian Maritime Centre of Expertise.
Shengyong Chen (Senior Member, IEEE) is a full professor at Tianjin University of Technology and the director of the Engineering Research Center of Learning-Based Intelligent System (Ministry of Education). He has been conducting research on vision sensors for robotics for more than 20 years. He obtained the Ph.D. degree in computer vision from City University of Hong Kong. From 2006 to 2007, he received a fellowship from the Alexander von Humboldt Foundation of Germany and worked at University of Hamburg, Germany. From 2008 to 2012, he worked as a visiting professor at Imperial College London and University of Cambridge, U.K. He has published over 300 scientific papers in international journals and conferences, including 80 papers in IEEE Transactions. He also published 10+ books in the past years and applied 100+ patents. He received the National Outstanding Youth Foundation Award of NSFC.
作者簡介(中文翻譯)
徐誠（IEEE 高級會員）於2020年6月在挪威科技大學（NTNU）海洋作業與土木工程系智能系統實驗室獲得工程學博士學位。從2020年6月到2022年3月，他在挪威吉奧維克的製造與土木工程系擔任博士後研究員及研究員。自2022年4月起，他在挪威智慧創新中心擔任正式研究員。他已申請並協調了超過5個由挪威研究委員會（NFR）、歐盟及產業支持的項目。他作為第一作者及共同作者發表了超過130篇論文，並在Springer出版了1本書，研究興趣包括海事作業中的數據分析與人工智慧、時間序列分析及風力發電機的預測性維護。
劉夢娜是中國天津科技大學計算機科學與工程學院的博士候選人，預計於2023年畢業。她擁有四年的算法工程師經驗，專注於設計算法和優化數據處理。她的研究興趣包括時間序列建模和數據挖掘。
施凡（IEEE 會員）是中國天津科技大學計算機科學與工程學院的教授。施博士於2012年在中國天津南開大學獲得博士學位。從2018年6月到2019年8月，他在西維吉尼亞大學擔任研究學者。他的研究興趣包括機器視覺、模式識別和光學。
劉秀峰於2012年在丹麥奧爾堡大學獲得計算機科學博士學位。他於2013年至2014年在滑鐵盧大學擔任博士後研究員，並在IBM加拿大擔任研究科學家。目前，他是丹麥技術大學技術、管理與經濟系的高級研究員。他的研究興趣包括智能電表數據分析、數據倉儲、能源資訊學和大數據。
張厚翔（IEEE 高級會員）於2003年和2011年2月分別在德國漢堡大學獲得機械與電子工程博士學位及資訊學的資格認證學位。目前，他是挪威科技大學（NTNU）工程學院海洋作業與土木工程系的正教授。自2004年以來，他一直在德國漢堡大學數位科學系擔任博士後研究員及高級研究員。2011年4月，他回到NTNU，並成為機電一體化的教授。從2011年到2016年，他還擔任挪威國家GIFT教授，專注於產品與系統設計，該職位由挪威海事專業中心資助。
陳勝勇（IEEE 高級會員）是天津科技大學的正教授，並擔任基於學習的智能系統工程研究中心（教育部）的主任。他在機器人視覺傳感器方面進行了超過20年的研究。他在香港城市大學獲得計算機視覺博士學位。2006年至2007年，他獲得德國亞歷山大·馮·洪堡基金會的獎學金，並在德國漢堡大學工作。2008年至2012年，他擔任英國倫敦帝國學院和劍橋大學的訪問教授。他在國際期刊和會議上發表了超過300篇科學論文，包括80篇在IEEE Transactions上發表的論文。他在過去幾年中出版了10本以上的書籍，並申請了100多項專利。他獲得了國家自然科學基金委員會的全國優秀青年基金獎。
