‘Be aware’: Manitoba business warning about counterfeit cash - CTV News

We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply. AbstractPredicting photovoltaic power generator outputs is not easy, especially when the values are near zero, because even very small errors can lead to large percentage errors. We introduce a new forecasting framework, ZAPP (Zero-Aware Photovoltaic Power Predictor), that handles near-zero errors while maintaining high prediction accuracy. The model does not rely on a single unified regression model but instead attaches two refinement stages to a base regression model. The first stage, called ZeroGate, predicts whether the output should be zero. The second refinement stage, the low-power MAPE reducer, fine-tunes the non-zero outputs near the zero level without significantly affecting scale-dependent regression metrics.