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RTP-GRU: Radiosonde Trajectory Prediction Model Based on GRU

Yinfeng Liu1Yaoyao Zhou2Jianping Du1Dong Liu1Jie Ren1Yuhan Chen3Fan Zhang2Jinpeng Chen2

1. Beijing HY Orient Detection Technology Co., Ltd.2. Beijing University of Posts and Telecommunications3. Beijing University of Technology

摘要:Radiosonde has always played a very important role in meteorological detection, so how to properly schedule the radiosonde to reach the sensitive region is an urgent problem. In this paper, deep learning is applied to this field for the first time to provide a basis for the reasonable scheduling of radiosonde by predicting the motion trajectory of radiosonde. Based on the radiosonde data from February 2019 to October 2019, this paper uses the radiosonde trajectory prediction model based on GRU(RTP-GRU) to predict the radiosonde trajectory in a period of time in the future. The experimental results show that this model has better performance than baseline methods such as RNN and LSTM. The results show that it is feasible and valuable to explore this field with deep learning method.
会议名称:

The 10th International Conference on Computer Engineering and Networks(CENet2020)

会议时间:

2020-10-16

会议地点:

中国陕西西安

  • 专辑:

    基础科学

  • 专题:

    气象学

  • DOI:

    10.26914/c.cnkihy.2020.037170

  • 分类号:

    P412.23

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