Graph-based models have also emerged as a promising avenue for water demand forecasting. A study developed a graph convolutional recurrent neural network (GCRNN) that captures both spatial and ...

Tourism demand forecasting is an essential aspect of managing ... For instance, a novel model called the spatial-temporal fused graph convolutional network (ST-FGCN) was developed to capture ...

A data scientist and entrepreneur with a background in finance and physics. Accurate demand forecasting is the linchpin of effective inventory, cost management and readiness. Knowing how much ...