Abstract: Fault diagnosis for high-dimensional industrial process data with strong nonlinear coupling remains challenging. Most existing graph convolutional network–based methods rely on static or ...

Abstract: The spatiotemporal dynamics of traffic forecasting make it a challenging task. In recent years, by adapting to the topology of traffic networks where road segments serve as nodes, graph ...

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Encode entities and relations in a knowledge graph using an RGCN-based GNN encoder Formulate learning path planning as a sequential decision-making problem Apply reinforcement learning to guide path ...