Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
This research project conducts a comprehensive comparative study of Random Forest and Gradient-Boosted Trees (XGBoost, CatBoost, and LightGBM) for predicting Indonesian public university tuition fees ...
Abstract: Iterative learning control (ILC) has demonstrated effectiveness in urban traffic signal control systems. However, conventional ILC methods typically require infinite iterations to achieve ...
With the accelerating pace of urbanization, the issue of air pollution has become increasingly severe. Notably, carbon monoxide (CO), as a prevalent harmful gas, poses potential threats to both human ...
Researchers from Japan's Waseda University have developed a new model that optimizes the route of electric delivery vehicles (EDVs) to maximize local PV surplus usage. For this purpose, the academics ...
ABSTRACT: An integrated model approaching to combining the BETR-GLOBAL model with a Random Forest method was developed in this research. Firstly, the BETR-GLOBAL model was employed to simulate the ...
State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Cancer Institute, Shanghai, China The high ...
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