A nowcasting model for the prediction of typhoon tracks based on a long short term memory neural network

GAO Song ZHAO Peng PAN Bin LI Yaru ZHOU Min XU Jiangling ZHONG Shan SHI Zhenwei

高松, 赵鹏, 潘斌, 李亚汝, 周敏, 徐江玲, 钟山, 史振威. 基于长短时记忆神经网络的台风路径临近预报模型[J]. 海洋学报英文版, 2018, 37(5): 8-12. doi: 10.1007/s13131-018-1219-z
引用本文: 高松, 赵鹏, 潘斌, 李亚汝, 周敏, 徐江玲, 钟山, 史振威. 基于长短时记忆神经网络的台风路径临近预报模型[J]. 海洋学报英文版, 2018, 37(5): 8-12. doi: 10.1007/s13131-018-1219-z
GAO Song, ZHAO Peng, PAN Bin, LI Yaru, ZHOU Min, XU Jiangling, ZHONG Shan, SHI Zhenwei. A nowcasting model for the prediction of typhoon tracks based on a long short term memory neural network[J]. Acta Oceanologica Sinica, 2018, 37(5): 8-12. doi: 10.1007/s13131-018-1219-z
Citation: GAO Song, ZHAO Peng, PAN Bin, LI Yaru, ZHOU Min, XU Jiangling, ZHONG Shan, SHI Zhenwei. A nowcasting model for the prediction of typhoon tracks based on a long short term memory neural network[J]. Acta Oceanologica Sinica, 2018, 37(5): 8-12. doi: 10.1007/s13131-018-1219-z

基于长短时记忆神经网络的台风路径临近预报模型

doi: 10.1007/s13131-018-1219-z
基金项目: The National Natural Science Foundation of China under contract Nos 61273245 and 41306028; the Beijing Natural Science Foundation under contract No. 4152031; the National Special Research Fund for Non-Profit Marine Sector under contract Nos 201405022-3 and 2013418026-4; the Ocean Science and Technology Program of North China Sea Branch of State Oceanic Administration under contract No. 2017A01; the Operational Marine Forecasting Program of State Oceanic Administration.

A nowcasting model for the prediction of typhoon tracks based on a long short term memory neural network

  • 摘要: 对台风路径进行准确预报能够有效降低人员与经济损失。长期以来我国气象部门观测到海量台风数据,然而,当前这些数据尚未得到充分的利用。基于机器学习算法的预测技术是一种有效的数据分析手段。利用1949-2011年间全部登陆中国大陆的台风数据,结合大数据与数据挖掘技术,训练一种长短时记忆神经网络(Long Short Term Memory,LSTM)模型,构建基于机器学习算法的台风路径预测模型。实验结果表明,本文算法能够提供6-24h内相对准确的台风路径临近预报,提高台风路径的预报精度。
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出版历程
  • 收稿日期:  2016-07-16
  • 修回日期:  2017-08-16

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