Journal of Thermal Engineering
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Performance Evaluation of Hybrid Nanofluid-Filled Cylindrical Heat Pipe by Machine Learning Algorithms
The current study attempts to predict the outlet temperature of a hybrid nanofluid heat pipe using three machine learning models, namely Extra Tree Regression (ETR), CatBoost Regression (CBR), and Light Gradient Boosting Machine Regression (LGBMR), in the Python environment. Based on 7000 experiment
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