| 机器学习在气象领域的应用现状与展望 |
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| 引用本文： | 杜智涛,姜明波,杜晓勇,周育峰,王鹏宇,张志标.机器学习在气象领域的应用现状与展望[J].气象科技,2021,49(6):930-941. |
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| 作者姓名： | 杜智涛 姜明波 杜晓勇 周育峰 王鹏宇 张志标 |
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| 作者单位： | 北京应用气象研究所，北京 100029 |
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| 摘 要： | 机器学习是人工智能的核心,是使计算机具有智能的根本途径之一。随着以深度学习为代表的机器学习算法取得突破,人工智能呈现了加速发展的趋势,在各行业取得了广泛的应用。机器学习在计算效率、准确性、可移植性、协同性、灵活性、易用性等方面具有较大的优势,下一步将有可能改变传统的气象观测模式,加速和改善气象观测数据的处理,改善数值天气预报质量以及推进地球科学的交叉融合。为更好地推动人工智能相关技术在气象领域的应用,本文从气象观探测、数值预报、危险天气识别与预警和卫星资料处理等方面对机器学习算法的应用现状进行了整理。
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| 关 键 词： | 机器学习 气象观探测 数值预报 危险天气 卫星资料 |
| 收稿时间： | 2020/12/3 0:00:00 |
| 修稿时间： | 2021/9/27 0:00:00 |
Application Status and Prospect of Machine Learning in Meteorology |
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| DU Zhitao,JIANG Mingbo,DU Xiaoyong,ZHOU Yufeng,WANG Pengyu,ZHANG Zhibiao.Application Status and Prospect of Machine Learning in Meteorology[J].Meteorological Science and Technology,2021,49(6):930-941. |
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| Authors: | DU Zhitao JIANG Mingbo DU Xiaoyong ZHOU Yufeng WANG Pengyu ZHANG Zhibiao |
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| Institution: | Beijing Institute of Applied Meteorology, Beijing 100029 |
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| Abstract: | Machine learning is the core of artificial intelligence (AI) and one of the fundamental ways to make computers intelligent. With breakthroughs in machine learning algorithms represented by deep learning, artificial intelligence has shown a trend of accelerated development and has been widely used in various industries. Machine learning has significant advantages in computational efficiency, accuracy, portability, coordination, flexibility, and ease of use. The next step will be to change the traditional weather observation mode and accelerate, and improve the processing of weather observation data and the quality of numerical weather prediction and promote the cross integration of earth sciences. In order to better promote the application of AI related technologies in meteorology, this paper summarizes the application status of machine learning algorithms from the aspects of meteorological observation, numerical forecast, dangerous weather identification and early warning and satellite data processing. |
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| Keywords: | machine learning weather observation numerical weather prediction dangerous weather satellite data |
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