An accurate prediction of imbalance prices is crucial for making well-informed decisions within short-term energy markets. This study proposes a two-stage probabilistic framework for the prediction of ...
Abstract: We propose a soft gradient boosting framework for sequential regression that embeds a learnable linear feature transform within the boosting procedure. At each boosting iteration, we train a ...
Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Recently, a research team led by Prof. Zhao Bangchuan from the Institute of Solid State Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, in collaboration with Prof. Xiao Yao ...
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