Traffic Speed Prediction Based on Spatial-Temporal Fusion Graph Neural Network
2021 IEEE 3rd International Conference on Frontiers Technology of Information and Computer (ICFTIC)(2021)
Abstract
Graph Convolutional Neural Network (GCN) has been widely used in traffic prediction research as an effective method for mining spatial dependencies. However, there are still challenges with traditional graph convolution methods, which are manifested in two ways: 1) The graph convolutional neural network-based approach is limited by the fixed adjacency matrix and cannot fully mine spatial-temporal ...
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Key words
Recurrent neural networks,Convolution,Fuses,Conferences,Graph neural networks,Convolutional neural networks,Kernel
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