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- W4229008876 abstract "The Ultimate Tensile Strength (MPa) of identical FSWed AA 6061 joints is determined using five Supervised Machine Learning regression-based and classification based techniques in this study. Tool Traverse Speed (mm/min), Tool Rotational Speed (RPM), and Axial Force are the three input parameters in the dataset (KN). The findings revealed that the Axial Force (KN) has a greater impact on the output, namely the Ultimate Tensile Strength (MPa). The algorithms' performance was compared using measures such as the Mean Absolute Error (MAE), Mean Square Error (MSE), Coefficient of Determination (R 2 ) value and F1- Score for ML based algorithms." @default.
- W4229008876 created "2022-05-08" @default.
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- W4229008876 date "2022-04-01" @default.
- W4229008876 modified "2023-09-26" @default.
- W4229008876 title "Determination of the Ultimate Tensile Strength (UTS) of friction stir welded similar AA6061 joints by using supervised machine learning based algorithms" @default.
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- W4229008876 doi "https://doi.org/10.1016/j.mfglet.2022.04.003" @default.
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