A Hybrid ARX and Deep Sequence Learning Architecture for Multivariate Industrial Time-Series Forecasting: An Application in Fluid Catalytic Cracking
Multi-parametric industrial time-series forecasting is important for predictive monitoring, soft sensing, and decision support in complex process industries. This study proposes a process-informed hybrid ARX-residual deep sequence architecture for short-horizon multi-output forecasting of fluid catalytic cracking unit...