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Multimodal Semisupervised Deep Graph Learning for Automatic Precipitation Nowcasting
Joint Authors
Miao, Kaichao
Zhang, Yali
Hu, Rui
Nian, Fudong
Zhang, Lei
Wang, Wei
Wang, Xiang
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-01
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Precipitation nowcasting plays a key role in land security and emergency management of natural calamities.
A majority of existing deep learning-based techniques realize precipitation nowcasting by learning a deep nonlinear function from a single information source, e.g., weather radar.
In this study, we propose a novel multimodal semisupervised deep graph learning framework for precipitation nowcasting.
Unlike existing studies, different modalities of observation data (including both meteorological and nonmeteorological data) are modeled jointly, thereby benefiting each other.
All information is converted into image structures, next, precipitation nowcasting is deemed as a computer vision task to be optimized.
To handle areas with unavailable precipitation, we convert all observation information into a graph structure and introduce a semisupervised graph convolutional network with a sequence connect architecture to learn the features of all local areas.
With the learned features, precipitation is predicted through a multilayer fully connected regression network.
Experiments on real datasets confirm the effectiveness of the proposed method.
American Psychological Association (APA)
Miao, Kaichao& Wang, Wei& Hu, Rui& Zhang, Lei& Zhang, Yali& Wang, Xiang…[et al.]. 2020. Multimodal Semisupervised Deep Graph Learning for Automatic Precipitation Nowcasting. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1194872
Modern Language Association (MLA)
Miao, Kaichao…[et al.]. Multimodal Semisupervised Deep Graph Learning for Automatic Precipitation Nowcasting. Mathematical Problems in Engineering No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1194872
American Medical Association (AMA)
Miao, Kaichao& Wang, Wei& Hu, Rui& Zhang, Lei& Zhang, Yali& Wang, Xiang…[et al.]. Multimodal Semisupervised Deep Graph Learning for Automatic Precipitation Nowcasting. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1194872
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1194872