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Spatio-temporal graph neural network based on time series periodic feature fusion for traffic flow prediction
Accurate prediction of the future traffic flow of a road section is helpful to disperse and guide vehicles in real-time, which can effectively improve t...
文献获取SCADA Data-Driven Spatio-Temporal Graph Convolutional Neural Network for Wind Turbine Fault Diagnosis
To solve abovementioned problems, a novel deep learning-based spatio-temporal graph convolutional neural network (STGCN) is developed for intelligent fa...
Spatiotemporal Fusion Prediction of Sea Surface Temperatures Based on the Graph Convolutional Neural and Long Short-Term Memory Netw...
Sea surface temperature (SST) prediction plays an important role in scientific research, environmental protection, and other marine-related fields. Howe...
Research on Industrial Process Fault Diagnosis Based on Deep Spatiotemporal Fusion Graph Convolutional Network
Second, to effectively extract spatiotemporal features from the data, the graph convolutional network (GCN) and the convolutional neural network (CNN) w...
基于图小波卷积神经网络的时空图挖掘模型
不充分的问题,提出一种基于图小波卷积神经网络的时空图挖掘模型(Spatial-temporal graph mining model based on graph wavelet convolutional neural network 简称...
Semi-supervised video object segmentation via an edge attention gated graph convolutional network
spatio-temporal graph modelgraph convolutional networkVideo object segmentation (VOS) exhibits heavy occlusions, large deformation, and severe motion bl...
Analyzing point cloud of coal mining process in much dust environment based on dynamic graph convolution neural network
Environmental perception is an important research direction of coal mine sustainable development. There is much dust in the underground working environm...
A hybrid model for spatiotemporal forecasting of PM2.5 based on graph convolutional neural network and long short-term memory
Increasing availability of data related to air quality from ground monitoring stations has provided the chance for data mining researchers to propose so...
Integrating external knowledge into aspect-based sentiment analysis using graph neural network
? 2022 Elsevier B.V.Aspect-based sentiment analysis aims to analyze the sentiment polarity of a given aspect. The graph convolutional neural network mod...
Nostradamus: A novel event propagation prediction approach with spatio-temporal characteristics in non-Euclidean space.
Hyperbolic graph convolutional recurrent neural networkSpatio-temporal characteristicsTime seriesThe prediction of event propagation has received extens...
