海浪预报方法研究进展  

Research progress of ocean waves forecasting method

作　　者：刘凡[1,2] 陆小敏[1,2] 徐丹 戴雯雯 李慧洲 LIU Fan;LU Xiaomin;XU Dan;DAI Wenwen;LI Huizhou(Key Laboratory of Coastal Disaster and Protection of Ministry of Education,Hohai University,Nanjing 211100,China;College of Computer and Information,Hohai University,Nanjing 211100,China;School of Computer Science,Jiangsu University of Science and Technology,Zhenjiang 212100,China)

机构地区：[1]河海大学海岸灾害与防护教育部重点实验室,江苏南京211100 [2]河海大学计算机与信息学院,江苏南京211100 [3]江苏科技大学计算机学院,江苏镇江212100

出　　处：《河海大学学报（自然科学版）》2021年第5期387-393,共7页Journal of Hohai University(Natural Sciences)

基　　金：河海大学海岸灾害与防护教育部重点实验室开放基金(20150009);江苏省自然科学基金(BK20191298)。

摘　　要：总结了海浪预报方法的分类和研究现状,对比分析了各类方法的优缺点。通过对比分析可知,半经验半理论预报法、经验统计预报法、数值预报法3类传统的海浪预报方法区域化显著,模型建立困难,并且对于实时性数据要求较高。此外,还分析了海浪预报的发展趋势,展望了大数据、人工智能和深度学习等新技术在海浪预报研究领域的应用前景。This study summarizes the classification,research status,advantages and disadvantages of existing ocean wave forecasting methods.Through the comparative analysis,it can be noted that the three traditional wave forecasting methods,semi-empirical and semi-theoretical forecasting method,empirical statistical forecasting method and numerical forecasting method,are significantly regionalized,face the challenge of modeling difficulties,and require high real-time data.Meanwhile,this paper also analyzes the developing trends and prospects the application foreground of some new techniques such as big data,artificial intelligence,and deep learning in the field of wave forecasting.

关 键 词：灾害性海浪 海浪预报 大数据 人工智能 深度学习 

分 类 号：TV124[水利工程—水文学及水资源]