IEEE

Mid-Term Load Forecasting With Minimal Data: An In-Context-Learning-Aware Approach Using ...

Abstract: Accurate mid-term load forecasting at the building level is vital for the strategic planning, operation, and sustainability of modern power systems. Machine learning approaches often require ...
IEEE

A Forecast-Driven Deep Learning Framework Using ICEEMDAN and PatchTST for Stock Prediction ...

Abstract: This paper introduces a novel hybrid framework, ICEEMDAN-PatchTST+FDPO, which integrates advanced signal decomposition, Transformer-based time series forecasting, and forecast-driven ...