A review of artificial intelligence in marine science - Song, Tao; Pang, Cong; Hou, Boyang; Xu, Guangxu; Xue, Junyu; Sun, Handan; Meng, Fan (Frontiers in Earth Science, 2023)
Human beings' utilization and exploitation of marine resources have promoted the development of marine science. Artificial intelligence technology is gradually applied to the ocean research field and, to some extent, complements traditional ocean forecasting models and ocean observation techniques. Intelligent ocean observation is achieved using satellite remote sensing data, sensor networking, and robotics combined with artificial intelligence technology. Machine learning and deep learning methods based on data-driven ocean elements can uncover factors ignored in theory and produce lightweight models for rapid forecasting of ocean elements. At the same time, machine learning and deep learning techniques in artificial intelligence complement and synergize with traditional numerical forecasting to optimize and error-correct the data and models of numerical methods and revise the numerical model results. In this paper, we utilize AI algorithmic models, as the main line and cite many application experiments to further systematically elaborate the research directions of combining machine learning and physical modeling ideas that have emerged in recent years. By sorting out several major applications of AI in marine field technologies, we combine examples to show the development paths in ocean observation, marine element forecasting, and numerical revisions. We look forward in several directions to the future development trend of AI in ocean observation, ocean element forecasting, and numerical revision is presented with examples.