SG-Net: A Spatiotemporal Graph Neural Network for Next-Step Supply-Chain Risk Monitoring via Demand Forecasting, Anomaly Detection, and Product-Relation Classification
Modern supply chains are highly interconnected, allowing local disruptions to spread across products, facilities, and distribution channels. This study introduces SG-Net, a spatiotemporal graph neural network that combines a relation-aware spatial encoder, a memory-augmented temporal encoder, and attention-based fusion...