Rainformer: Features Extraction Balanced Network for Radar-Based Precipitation Nowcasting-Reference-Cited by-同舟云学术

Rainformer: Features Extraction Balanced Network for Radar-Based Precipitation Nowcasting

Published:2022 Issue: Volume:19 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Bai Cong¹^ORCID,Sun Feng¹,Zhang Jinglin²^ORCID,Song Yi³,Chen Shengyong⁴^ORCID

Affiliation:

1. College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China

2. School of Control Science and Engineering, Shandong University, Jinan, China

3. Piesat Information Technology Company Ltd, Beijing, China

4. College of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China

Funder

National Key Research and Development Program of China

Zhejiang Provincial Natural Science Foundation

Key Research and Development Program of Jiangsu Province

Joint Open Research of Key Laboratory of Meteorological Disaster (KLME) and Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/9651998/09743916.pdf?arnumber=9743916

Reference19 articles.

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4. Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics

5. PFST-LSTM: A SpatioTemporal LSTM Model With Pseudoflow Prediction for Precipitation Nowcasting

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