ST-GRF: Spatiotemporal graph neural networks for rainfall forecasting

Author:

Zhang Fang-Hao,Shao Zhi-GangORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Signal Processing,Artificial Intelligence,Applied Mathematics,Computer Vision and Pattern Recognition,Statistics, Probability and Uncertainty,Computational Theory and Mathematics

Reference64 articles.

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2. A tutorial survey of architectures, algorithms, and applications for deep learning;Deng;APSIPA Trans. Signal Inf. Process.,2014

3. A physical statistic model for predicting the rainfall during flood season in Sichuan-Chongqing region;Zhengfeng;Chin. J. Atmos. Sci.-Chin. Ed.,2004

4. A deep-learning based precipitation forecasting approach using multiple environmental factors;Zhang,2017

5. Combined gamma and M-test-based ANN and ARIMA models for groundwater fluctuation forecasting in semiarid regions;Choubin;Environ. Earth Sci.,2017

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