... framework to optimize two key chemical vapor deposition performance metrics: film deposition rate and thickness uniformity. Design/methodology/approach Building on previous work that benchmarked several machine learning models against computational fluid dynamics ( CFD )–generated data, the XGBoost...

... (30% biodiesel, 10% biogas, 60% Jet A fuel), respectively. All the blends are tested already in the previous study, and the results were trained using the ML models here, and the comparison was made.The machine learning models used were XGBoost, random forest and ridge regression. These models were...

... XGBoost is an efficient gradient boosting tree algorithm suitable for handling various prediction problems, including the prediction of flight arrival delay durations. When constructing an XGBoost model, some key features are usually selected, such as planned flight time, previous flight delay time...