Abstract: Federated Learning (FL) is an emerging computing paradigm to collaboratively train Machine Learning (ML) models across multi-source data while preserving privacy. The major challenge of ...
Researchers at Central South University in China have developed a new model to improve ultra-short-term photovoltaic (PV) power prediction, as detailed in their publication in Frontiers in Energy. In ...
A new study published in the Journal of Orthopaedic Research indicates that an artificial intelligence–based model trained on basic blood and lab test data as well as basic demographic data can ...
ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
ABSTRACT: The diversity of snail intermediate hosts of schistosomes and infection rates are influenced by environmental determinants. Knowledge of these local environmental determinants is an ...
Abstract: This research aims to formulate an optimal control algorithm for a hydrothermal air-conditioning system, with the objective of minimizing energy consumption while simultaneously ensuring ...
Traditional multi-pass cells (MPCs) rely on grid search algorithms for design, which suffer from problems such as long design time and high computational cost. Additionally, these conventional methods ...
I have successfully run the deep learning models. However, when I run the Gradient Boosting Regression model, the predictions collapse into a straight flat line. I would like to understand why this ...
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