Prediction of Surface Roughness in End Milling Process Using Intelligent Systems: A Comparative Study

Table 3

Experimental results for training data (Lo [12] and Ho et al. [13]).

𝑚	Experimental results
	𝑆𝑚	𝐹𝑚	𝐷𝑚	𝑅𝑚
1	750	6	0.01	65
2	750	6	0.03	63
3	750	6	0.05	72
4	750	12	0.01	144
5	750	12	0.03	102
6	750	12	0.05	94
7	750	18	0.01	185
8	750	18	0.03	147
9	750	18	0.05	121
10	750	24	0.01	187
11	750	24	0.03	170
12	750	24	0.05	172
13	1000	6	0.01	58
14	1000	6	0.03	78
15	1000	6	0.05	62
16	1000	12	0.01	130
17	1000	12	0.03	84
18	1000	12	0.05	92
19	1000	18	0.01	138
20	1000	18	0.03	124
21	1000	18	0.05	86
22	1000	24	0.01	163
23	1000	24	0.03	153
24	1000	24	0.05	142
25	1250	6	0.01	50
26	1250	6	0.03	63
27	1250	6	0.05	71
28	1250	12	0.01	101
29	1250	12	0.03	99
30	1250	12	0.05	85
31	1250	18	0.01	115
32	1250	18	0.03	92
33	1250	18	0.05	95
34	1250	24	0.01	155
35	1250	24	0.03	109
36	1250	24	0.05	121
37	1500	6	0.01	37
38	1500	6	0.03	56
39	1500	6	0.05	56
40	1500	12	0.01	88
41	1500	12	0.03	82
42	1500	12	0.05	94
43	1500	18	0.01	119
44	1500	18	0.03	87
45	1500	18	0.05	104
46	1500	24	0.01	119
47	1500	24	0.03	103
48	1500	24	0.05	109