Multistation Wind Speed Forecasting Based on Dynamic Spatiotemporal Graph Convolutional Networks

Multistation Wind Speed Forecasting Based on Dynamic Spatiotemporal Graph Convolutional Networks

Wind speed forecasting is significant in practical applications such as energy dispatch and meteorological early warning systems. However, spatiotemporal correlations of wind speed are dynamically influenced by weather conditions, seasonal variations, and diurnal fluctuations, resulting in constantl...

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Bibliographic Details
Main Authors: Jianhong Gan, Runqing Kang, Xun Deng, Chentao Mao, Zhibin Li, Peiyang Wei, Chunjiang Wu, Tongli He
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Adjacency matrix
dynamic time warping (DTW)
graph convolution
particle swarm optimization (PSO)
wind speed forecasting
Online Access:https://ieeexplore.ieee.org/document/11078154/
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