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

Table 9

The consequent parameters of ANFIS FO Sugeno model trained with HL algorithm.

Rule no.	𝑝𝑖	𝑞𝑖	𝑟𝑖	𝑡𝑖
1	–0.3475	0.1141	0.09476	0.4712
2	0.4908	0.01827	0.03587	0.06537
3	–0.5326	0.082	0.3158	0.3164
4	–0.142	0.6265	0.1154	0.508
5	–0.8807	0.3169	0.3492	0.5938
6	0.3319	–0.05292	0.1754	0.1892
7	–1.996	–0.05069	0.4055	1.978
8	–0.3329	0.3839	0.2737	0.5203
9	–1.28	1.041	0.2528	0.2626
10	0.2578	0.07892	0.05012	0.2143
11	0.2012	0.08151	0.1871	0.3131
12	0.2403	0.05555	0.1689	0.1762
13	0.673	–1.131	0.1542	0.7394
14	0.4164	0.01532	0.1737	0.3085
15	0.1619	–0.5922	0.2246	0.231
16	–1.471	5.782	–0.4443	–2.232
17	0.008048	0.6415	–0.0189	–0.08517
18	–0.4688	2.999	–0.7868	–0.7847
19	–0.215	0.09277	0.07536	0.367
20	0.1457	0.03197	0.06851	0.1165
21	–0.3208	0.07498	0.2976	0.2996
22	–0.3354	0.3712	0.1312	0.5879
23	–0.4769	0.2513	0.3433	0.588
24	0.1199	0.1176	0.1524	0.1659
25	0.3456	–0.0816	0.07721	0.3656
26	–0.1232	0.3988	0.1172	0.1992
27	0.008071	0.06087	0.2541	0.2582