TableĀ 7

Statistical data using three different algorithms for the axial cutting forces

AlgorithmNumber of neuronsTraining dataTesting data
RMSER2MEPRMSER2MEP
LM50.0307540.9981934.8850960.0414970.9965946.78182
LM60.0325520.9980045.2138140.0384620.9970226.195043
LM70.0300920.9983074.7045580.0422880.9962546.502323
LM80.0301370.9983124.735550.0396430.9968055.944426
LM90.0300710.9982944.6613440.0392030.9968436.372841
LM100.0302250.9982914.6818070.0407090.9967686.327074
SCG50.0722440.9899913.1010280.0780620.98879814.309749
SCG60.0716650.98874712.4978790.0805760.98666511.671692
SCG70.0639150.99188911.045790.0759260.98881813.253753
SCG80.0747550.99029413.8310710.086340.98730315.132508
SCG90.0693960.99075712.4163540.0856450.98503815.559988
SCG100.0684760.9904412.5045560.0809750.98747615.024751
BR50.0475140.9946567.1728960.0544380.9935248.175147
BR60.0510350.9933327.7345090.0534460.9931388.739134
BR70.0333730.9979255.4092920.0418120.9965866.594196
BR80.0422320.9963766.5655980.0486040.9946247.627173
BR90.0456490.9951296.9560580.0572610.9915818.627781
BR100.0801310.98199114.3397920.0884710.98102215.922456

Source(s): Authors own work

or Create an Account

Close Modal
Close Modal