机器学习在海上结构物运动预报中的应用综述

Applications of machine learning in motion prediction of marine structures: review and outlook

关键词:  机器学习  运动预测  不规则波预测  船舶运动  海上平台运动

Key words:  machine learning  motion prediction  irregular wave prediction  ship movement  offshore platform movement

摘要:

为研究机器学习在海上结构物运动预报的发展现状及其亟需解决的关键问题,文中对近10年来海洋工程领域针对海上结构物运动预报的研究进行了全面的论述。随着海上结构物运动预报的需求不断扩大,基于流体力学理论的传统预测方法在预报精度与预报实时性上不能同时满足实际应用需求,而机器学习方法的出现,使精确预测未来时刻的运动响应并依据该响应实现结构物的超前控制成为现实。文中基于预报方法的建模原理将其分为统计回归方法、一般神经网络方法、智能神经网络方法与混合预测方法4类,并对4类方法进行了全面的回顾、分析和综合。最后,分析了当前存在的不足与问题,并从预报方法、框架以及数据集等方面给出了未来发展方向,可为船舶、海上平台等海上结构物运动预测领域的发展提供参考。研究表明:机器学习在海上结构物运动预报领域的研究尚处于相对初始阶段,仍有许多技术难题亟需解决,但随着AI大模型的大力发展与本领域研究学者对机器学习研究的不断深入,可为本领域特色预报方法的开发提供坚实基础。

Abstract:

To study the development status and the key problems that need to be solved urgently of machine learning in motion prediction of marine structures, this paper comprehensively discusses the research on motion prediction of marine structures in the field of marine engineering in the past ten years. With the increasing demand for motion prediction of marine structures, the traditional prediction methods based on fluid mechanics theory cannot meet the practical application requirements in terms of both prediction accuracy and real-time performance. The emergence of machine learning methods makes it possible to accurately predict the future motion response and realize advanced control of structures according to the response. Based on the modeling principles of forecasting methods, they are classified into four categories: statistical regression methods, general neural network methods, intelligent neural network methods and hybrid forecasting methods, and the four categories of methods are comprehensively reviewed, analyzed and synthesized. Finally, the existing shortcomings and problems are analyzed, and the future development directions are given from the aspects of prediction method, framework and data set, which can provide reference for the development of motion prediction of marine structures such as ships and offshore platforms. The research shows that the research of machine learning in the field of marine structure motion prediction is still in the initial stage, and there are still many technical problems to be solved. However, with the vigorous development of AI large model and the deepening of machine learning research by researchers in this field, it can provide a solid foundation for the development of characteristic prediction methods in this field.