Table 4.

Central composite design (CCD) with experimental responses and predicted responses.

S.No	Parameters					Experimental value*					RSM prediction					ANFIS prediction					Machine learning algorithm prediction
	X1	X2	X3	X4	X5	y1	y2	y3	y4	y5	y1	y2	y3	y4	y5	y1	y2	y3	y4	y5	y1	y2	y3	y4	y5
1	0.25	65	23	40	70	667.67	445.65	78.95	75.65	70.04	695.15	441.62	82.41	77.2256	72.3434	717	471	85.6	81.3	75.7	666.87	449.63	79.57	75.66	70.28
2	0.155	62.5	23	40	70	672.45	454.65	81.89	77.85	71.52	752.64	469.42	82.22	76.72	71.52	632	426	76.5	72.8	67.3	669.70	455.11	81.18	76.93	71.14
3	0.155	67.5	23	40	70	670.13	448.76	79.05	76.45	70.43	732.76	467.24	83.24	78.544	73.5081	634	427	76.8	73.3	67.8	668.34	451.40	79.52	76.10	70.49
4	0.155	65	23	40	67.5	658.65	463.34	80.34	73.78	70.37	751.71	472.56	82.26	77.4991	72.2171	635	427	76.7	73.1	67.6	662.44	458.40	80.11	74.71	70.42
5	0.155	65	23	40	72.5	659.67	462.34	81.32	74.71	70.24	735.34	465.39	83.61	78.0947	73.176	632	426	76.7	73	67.5	663.29	458.12	80.85	75.40	70.39

*All the experiments repeated three times.