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浙江大学学报（理学版）
浙江大学学报（理学版）  2020, Vol. 47 Issue (2): 196-202    DOI: 10.3785/j.issn.1008-9497.2020.02.010
地球科学     
基于神经网络集合预报的台风路径预报优化
周笑天1,2, 张丰1,2, 杜震洪1,2, 刘仁义1,2
1.浙江大学 浙江省资源与环境信息系统重点实验室，浙江 杭州 310028
2.浙江大学 地理信息科学研究所， 浙江 杭州 310027
Optimization of typhoon track prediction based on neural network ensemble prediction
ZHOU Xiaotian1,2, ZHANG Feng1,2, DU Zhenhong1,2, LIU Renyi1,2
1.Zhejiang Provincial Key Lab of GIS, Zhejiang University, Hangzhou 310028, China
2.Department of Geographic Information Science, Zhejiang University, Hangzhou 310027, China
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摘要： 针对目前台风路径预报研究中存在的预报精度不高、预报时次高耦合等缺陷，提出了一种基于神经网络集合预报的台风路径预报优化模型。运用混合模式集合预报思想和反向传播的多层前馈训练机制，充分挖掘数据特征，解决了单集合预报的固化性问题和单神经网络预报模型的随机性问题，为现有台风数值预报方法和人工智能技术的结合提供了新思路。以2018年活动在西北太平洋、南海地区的台风为样本进行对比实验，结果表明，60 h内的预报精度均得到了提高，一定程度上反映了该模型的实际应用价值。
关键词： 集合预报;  混合模式;  神经网络    
Abstract: An optimization model of typhoon track prediction based on ensemble prediction of neural network is presented in the paper to overcome the shortcomings of the current typhoon track prediction models, such as inadequate prediction accuracy and high coupling of forecast times. The proposed model uses the idea of ensemble prediction of mixed model and multi-layer feedforward training mechanism of reverse propagation to fully mine data characteristics, and solves the solidification problem of single ensemble prediction model as well as the randomness problem of the single neural network forecasting model, which provides a new idea for the combination of the existing typhoon numerical forecasting method and artificial intelligence technology. The typhoon activity in the Northwest Pacific and South China Sea in 2018 is taken as a sample for comparative experiments. The results show that the forecasting accuracy of the model regarding a period of 60 hours has been improved , which reflects the practical application value of the model to a certain extent.
Key words: ensemble prediction    hybrid model    neural network
收稿日期: 2019-06-24 出版日期: 2020-03-25
CLC:  P456  
基金资助: 国家重点研发计划项目（2018YFB0505000）.
通讯作者: ORCID:http://orcid.org/0000-0001-9449-0415，E-mail：duzhenhong@zju.edu.cn.     E-mail: duzhenhong@zju.edu.cn
作者简介: 周笑天 (1994—)，ORCID:http://orcid.org/0000-0002-8147-8027,男，硕士研究生，主要从事时空大数据挖掘研究.
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引用本文:

周笑天, 张丰, 杜震洪, 刘仁义. 基于神经网络集合预报的台风路径预报优化[J]. 浙江大学学报（理学版）, 2020, 47(2): 196-202.

ZHOU Xiaotian, ZHANG Feng, DU Zhenhong, LIU Renyi. Optimization of typhoon track prediction based on neural network ensemble prediction. Journal of Zhejiang University (Science Edition), 2020, 47(2): 196-202.

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https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2020.02.010    或    https://www.zjujournals.com/sci/CN/Y2020/V47/I2/196

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