Complexity / 2017 / Article / Tab 3

Research Article

Coping with Complexity When Predicting Surface Roughness in Milling Processes: Hybrid Incremental Model with Optimal Parametrization

Table 3

Comparative study with conventional models.

Theoretical model SCEC model [14]Taguchi model [14]HIM + SA
Ra (μm)Raκ (μm)Prediction error (%)Ra (μm) (μm)Prediction error (%)Ra (μm)Raη (μm)Prediction error (%)Ra (μm) (μm)Prediction error (%)

0.1600.18213.7500.1110.1153.6040.2490.2698.0320.3410.3410.015
0.2060.27332.5240.1530.17111.7650.1950.15918.4620.1570.1560.414
0.2220.36463.9640.1970.2075.0760.2190.2210.9130.2850.2860.312
0.1360.18233.8240.0950.10510.5260.2220.25715.7660.4720.4730.199
0.1940.27340.7220.1580.1551.8990.1360.12210.2940.2570.2560.261
0.2050.36477.5610.1900.1843.1580.1680.1701.1900.5760.5780.366
0.1260.18244.4440.0810.0832.4690.1110.12310.8110.3630.3630.019
0.1680.27362.5000.1360.1360.0440.1580.12620.2530.2600.2600.150
0.2030.36479.3100.1710.1731.1700.1710.1662.9240.7300.7320.260