Contextual Background Estimation for Explainable AI in Temperature Prediction

Applied Sciences, Год журнала: 2025, Номер 15(3), С. 1057 - 1057

Опубликована: Янв. 22, 2025

Accurate weather prediction and electrical load modeling are critical for optimizing energy systems mitigating environmental impacts. This study explores the integration of novel Mean Background Method Estimation with Explainable Artificial Intelligence (XAI) aim to enhance evaluation understanding time-series models in these domains. The or temperature predictions regression-based problems. Some XAI methods, such as SHAP, require using base value model background provide an explanation. However, contextualized situations, default is not always best choice. selection can significantly affect corresponding Shapley values. paper presents two innovative methods designed robust context-aware explanations regression problems, addressing gaps interpretability. They be used improve make more conscious decisions made by that use data.

Язык: Английский

Sustainable AI-driven wind energy forecasting: advancing zero-carbon cities and environmental computation

Artificial Intelligence Review, Год журнала: 2025, Номер 58(6)

Опубликована: Март 29, 2025

Язык: Английский