Results 1 to 10 of about 50,507 (118)
STMP-Net: A Spatiotemporal Prediction Network Integrating Motion Perception [PDF]
Sensors, 2023 This article proposes a video prediction network called STMP-Net that addresses the problem of the inability of Recurrent Neural Networks (RNNs) to fully extract spatiotemporal information and motion change features during video prediction.
Suting Chen, Ning Yang
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Advances in spatiotemporal graph neural network prediction research
International Journal of Digital Earth, 2023 Being a kind of non-Euclidean data, spatiotemporal graph data exists everywhere from traffic flow, air quality index to crime case, etc. Unlike the raster data, the irregular and disordered characteristics of spatiotemporal graph data have attracted the ...
Yi Wang
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Global Energy Interconnection, 2022 Owing to the expansion of the grid interconnection scale, the spatiotemporal distribution characteristics of the frequency response of power systems after the occurrence of disturbances have become increasingly important.
Dengyi Huang +3 more
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PLoS ONE, 2023 The primary cause of hazy weather is PM2.5, and forecasting PM2.5 concentrations can aid in managing and preventing hazy weather. This paper proposes a novel spatiotemporal prediction model called SpatioTemporal-Informer (ST-Informer) in response to the ...
Zhanfei Ma +6 more
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Atmosphere, 2021 Multi-source meteorological data can reflect the development process of single meteorological elements from different angles. Making full use of multi-source meteorological data is an effective method to improve the performance of weather nowcasting. For
Fuhan Zhang, Xiaodong Wang, Jiping Guan
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International Journal of Digital Earth, 2023 The anomalous movements of glaciers cause disasters, such as debris flows and landslides. It is very important to assess the glacier movements and their future trends. Glacier velocity refers to movement process. The current research aims to analyse past
Yali Zhang +6 more
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Seven-day sea surface temperature prediction using a 3DConv-LSTM model
Frontiers in Marine Science, 2022 Due to the application demand, users have higher expectations for the accuracy and resolution of sea surface temperature (SST) products. Recent advances in deep learning show great advantages in exploiting massive ocean datasets, and provides ...
Li Wei, Lei Guan, Lei Guan, Lei Guan
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Power Prediction of Photovoltaic Clusters Based on Spatio-Temporal Feature Extraction and Cross-Modal Fusion [PDF]
Dianli jianshe[Objective] Photovoltaic （PV） power forecasting is a critical component of grid-connected PV dispatch and optimization. However， existing forecasting methods inadequately capture the spatial correlations between power plants， particularly in scenarios ...
WANG Jian, LIU Huiyuan, ZHANG Zhanxi, SHEN Fu, WANG Kaizheng, CAI Zilong
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Accurate and comprehensive vegetation prediction methods are essential for effective agricultural planning and budgeting. Most existing vegetation prediction methods rely on sampling points rather than on overall spatiotemporal characteristics, making it
Lifeng Zhang +5 more
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MSSTNet: A Multi-Scale Spatiotemporal Prediction Neural Network for Precipitation Nowcasting
Remote Sensing, 2022 Convolution-based recurrent neural networks and convolutional neural networks have been used extensively in spatiotemporal prediction. However, these methods tend to concentrate on fixed-scale spatiotemporal state transitions and disregard the complexity
Yuankang Ye +4 more
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