数字海洋与水下攻防2024,Vol.7Issue(5) :536-545.DOI:10.19838/j.issn.2096-5753.2024.05.010

海洋智能预报发展应用及装备展望

Equipment Development and Application Prospects of Ocean Intelligent Forecasting

罗潇 周河宇 赵旻晟 潘州 梁祺 张文峰
数字海洋与水下攻防2024,Vol.7Issue(5) :536-545.DOI:10.19838/j.issn.2096-5753.2024.05.010

海洋智能预报发展应用及装备展望

Equipment Development and Application Prospects of Ocean Intelligent Forecasting

罗潇 1周河宇 2赵旻晟 3潘州 3梁祺 3张文峰4
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作者信息

  • 1. 海军装备部驻广州地区军事代表局,广东 广州 510210
  • 2. 中国船舶集团有限公司第七一〇研究所,湖北 宜昌 443003;清江创新中心,湖北 武汉 430076
  • 3. 天津航海仪器研究所,天津 300131
  • 4. 广船国际有限公司,广东 广州 510382
  • 折叠

摘要

全球海洋预报大模型与大数据应用、气象预报模型发展密不可分,简述了基于深度学习的人工智能技术在气象预报、海洋预报中的应用和特点.重点报告了我国各科研机构在全球海洋预报大模型领域的研究现状.结果表明,当前在数据驱动建模、海洋大数据分析、海洋要素智能预报等领域研究达到世界领先水平,预报周期、关键预测准确率超过目前世界先进预报系统.最后,结合海洋强国战略,分析并展望了海洋智能预报在装备应用领域发展中存在的挑战,考虑海洋安全背景下针对数据处理和装备应用等方面的研究方向.

Abstract

The development of global ocean forecasting models is closely related to the application of big data and meteorological forecasting models.In this article,the application and characteristics of artificial intelligence technology based on deep learning in meteorological and ocean forecasting is briefly described.The article focuses on the research status of various scientific research institutions in China in the field of global ocean forecasting big models.The results indicate that current research in data-driven modeling,ocean big data analysis,and intelligent forecasting of ocean elements has reached a world leading level,with forecasting cycles and key prediction accuracy exceeding advanced forecasting systems in the world.Finally,based on the strategy of building a strong maritime nation,the challenges in the development of ocean intelligent forecasting in the field of equipment application are analyzed and discussed,and the research directions for data processing and equipment application in the context of maritime security are put forward.

关键词

海洋预报/智能预报/大模型/人工智能

Key words

ocean forecasting/intelligent forecasting/big model/artificial intelligence

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出版年

2024
数字海洋与水下攻防
中国船舶重工集团公司第七研究院第七一0研究所

数字海洋与水下攻防

影响因子:0.134
ISSN:2096-5753
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