Prediction of surface roughness in milling with a ball end tool using an artificial neural network

OBRABOTKAMETALLOV MATERIAL SCIENCE Том 23 № 3 2021 EQUIPMEN . INSTRUM TS Vol. 7 No. 2 2025 In this study, we examine the effect of activation function on the performance of eight neural network models in predicting Rz (Fig. 4). Loss function reflects model training efficiency. The ReLU activation speeds training but requires monitoring of both Train Loss and Validation Loss. Low training loss with high validation loss indicates Fig. 4. Learning rates of various configurations

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