Global trade network prediction based on spatiotemporal graph neural network and gradient boosting model
This paper addresses the challenges of nonlinearity, spatiotemporal dependence, and coupling with external factors in global trade network forecasting. A hybrid model (ST-GBDT) integrating spatiotemporal graph neural networks and gradient boosting decision trees is proposed. This model constructs a multi-channel spat...
Tian-Wen Zhao, Guo-Qing Chen, Li-Li Zhang et al.
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