A self-attention integrated spatiotemporal LSTM approach to edge-radar echo extrapolation in the Internet of Radars

Author:

Yang Zhiyun,Wu Hao,Liu QiORCID,Liu Xiaodong,Zhang Yonghong,Cao Xuefei

Publisher

Elsevier BV

Subject

Applied Mathematics,Control and Systems Engineering,Electrical and Electronic Engineering,Computer Science Applications,Instrumentation

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. DenMerD: a feature enhanced approach to radar beam blockage correction with edge-cloud computing;Journal of Cloud Computing;2024-02-05

2. An Long Short-Term Memory Model with Multi-Scale Context Fusion and Attention for Radar Echo Extrapolation;Remote Sensing;2024-01-17

3. A Radar Echo Extrapolation Model Based on a Dual-Branch Encoder–Decoder and Spatiotemporal GRU;Atmosphere;2024-01-14

4. Enhancing Radar Echo Extrapolation by ConvLSTM2D for Precipitation Nowcasting;Sensors;2024-01-11

5. A Real-Time Load Forecasting Approach Based on Graph Convolution Neural Network in a Distributed IoT Energy System;2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech);2023-11-14

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