GitHub1 年
Traffic Graph Convolutional Recurrent Neural Network
The 2nd version of the structure of Traffic Graph Convolutional LSTM (TGC-LSTM). is the K-th order adjacency matrix is the Free Flow Reachability matrix defined ... 1st version of the High-order Graph ...
GitHub1 年
Exploring urban form through graph neural networks
Graph theory has long provided the basis for the computational modelling of urban flows and networks and, thus, for the study of urban form. The development of graph-convolutional neural networks ...
IEEE3 天
Advancing Graph Convolution Network with Revised Laplacian Matrix
Abstract: Graph convolution networks are extremely efficient ... Most existing models mainly focus on redefining the complicated network structure, while ignoring the negative impact of low-quality ...
Frontiers1 个月
Utilizing a Two-Dimensional Data-Driven Convolutional Neural Network for Long-Term ...
On this basis, a two-dimensional data-driven convolutional neural network model (2DD-CNN) is proposed ... this method preserves the time series information in the form of matrix arrangement. At the ...
IEEE1 年
Xing-Xing Xing
Diagonal Matrix,Eigenvectors,Embedding Representation,Field Games,Final Prediction,Form Of A Heatmap,Game Experience,Gameplay,Gated Recurrent Unit,Graph Convolution,Graph Convolutional Network ...