Barrier-enforced multi-objective optimization for direct point and sharp interval forecasting

ArXi:2604.18492v1 Announce Type: new This paper proposes a multi-step probabilistic forecasting framework using a single neural-network based model to generate simultaneous point and interval forecasts. Our approach ensures non-crossing prediction intervals (PIs) through a model structure design that strictly satisfy a target coverage probability (PICP) while maximizing sharpness.