Table 10 Input parameters considered for RBFNN model 1 (speed rate, feed rate, depth of cut, tool flank wear, and 15 GLCM features) for surface roughness prediction and comparison of R_a for stylus measured and predicted values along with errors obtained (randomly selected data).

From: Image-processing-based model for surface roughness evaluation in titanium based alloys using dual tree complex wavelet transform and radial basis function neural networks

Exp. no.	Speed	Feed	DOC	Flank Wear	F1	F 2	F 3	F 4	F 5	F 6	F 7	F 8	F 9	F 10	F 11	F 12	F 13	F 14	F 15	Direct method R_a	Image processing R_a	Error (%)
1	150	0.15	0.8	0.080	62.2207	0.0644	0.6932	0.8938	0.0606	0.7399	0.5614	0.9703	0.8549	62.0018	15.7668	233.0211	0.5134	0.0644	0.2316	0.8337	0.8217	1.44
2	150	0.20	0.8	0.120	61.3676	0.0301	0.9263	6.5926	0.0284	0.7165	0.6190	0.9861	0.8383	61.1361	15.6433	227.2036	0.5962	0.0301	0.1299	1.3688	1.3513	1.28
3	150	0.25	0.8	0.100	60.9544	0.0191	0.9658	13.3247	0.0176	0.7120	0.6293	0.9914	0.8359	60.6862	15.5801	225.0503	0.6150	0.0191	0.0888	1.2584	1.2459	0.99
4	175	0.15	0.8	0.095	61.2359	0.0122	0.9734	9.5143	0.0120	0.7234	0.5781	0.9941	0.8416	60.9789	15.6220	227.4894	0.5694	0.0122	0.0650	0.5510	0.5610	1.81
5	175	0.20	0.8	0.115	61.0546	0.0206	0.9584	8.3575	0.0199	0.7140	0.6151	0.9901	0.8368	60.8011	15.5972	225.8803	0.6001	0.0206	0.0982	0.7025	0.6860	2.35
6	175	0.25	0.8	0.085	58.7128	0.1153	0.7964	4.2786	0.1143	0.4544	1.0866	0.9430	0.6234	58.5031	15.2954	205.2547	1.0042	0.1153	0.3577	0.9282	0.9062	2.37
7	200	0.15	0.8	0.130	61.3803	0.0240	0.9341	4.4595	0.0225	0.7107	0.5953	0.9890	0.8325	61.1361	15.6474	227.8241	0.5769	0.0240	0.1080	0.4703	0.4863	3.40
8	200	0.20	0.8	0.135	61.6126	0.0217	0.9316	3.4715	0.0215	0.7270	0.5567	0.9893	0.8428	61.3461	15.6799	229.7803	0.5416	0.0217	0.1042	1.3688	1.3368	2.34
9	200	0.25	0.8	0.090	61.3160	0.0148	0.9643	6.4149	0.0131	0.7253	0.5650	0.9937	0.8423	61.0657	15.6354	228.2919	0.5530	0.0148	0.0694	0.8172	0.8317	1.77
10	150	0.15	1.0	0.095	61.2878	0.0136	0.9690	7.5179	0.0132	0.7256	0.5746	0.9935	0.8433	61.0296	15.6302	227.8257	0.5649	0.0136	0.0704	0.6332	0.6201	2.07
11	150	0.20	1.0	0.075	60.7035	0.0457	0.9188	11.9257	0.0457	0.6615	0.7589	0.9771	0.8040	60.4605	15.5493	220.7697	0.7273	0.0457	0.1857	0.6407	0.6216	2.98
12	150	0.25	1.0	0.106	61.5523	0.0264	0.9295	5.7243	0.0264	0.7336	0.5838	0.9868	0.8494	61.3035	15.6688	228.8281	0.5657	0.0264	0.1221	0.6815	0.6670	2.13
13	175	0.15	1.0	0.120	60.9303	0.0232	0.9588	12.0950	0.0231	0.7130	0.6389	0.9884	0.8371	60.6723	15.5770	224.7128	0.6234	0.0232	0.1102	0.6455	0.6305	2.32
14	175	0.20	1.0	0.085	60.5119	0.0521	0.8844	4.8297	0.0520	0.6143	0.7866	0.9740	0.7650	60.2667	15.5323	219.3455	0.7506	0.0521	0.2046	0.5958	0.5857	1.70
15	175	0.25	1.0	0.085	61.2179	0.0144	0.9681	8.5993	0.0139	0.7199	0.5859	0.9932	0.8393	60.9571	15.6204	227.2433	0.5753	0.0144	0.0732	0.7572	0.7381	2.52
16	200	0.15	1.0	0.100	59.0152	0.1258	0.7896	6.0400	0.1235	0.4693	1.1000	0.9386	0.6488	58.8211	15.3335	206.2643	1.0089	0.1258	0.3780	0.3910	0.3809	2.58
17	200	0.20	1.0	0.090	61.3525	0.0387	0.8980	4.3292	0.0372	0.7060	0.6398	0.9817	0.8313	61.0935	15.6438	226.7144	0.6107	0.0387	0.1600	0.6224	0.6186	0.61
18	200	0.25	1.0	0.115	60.1439	0.0472	0.9166	8.9125	0.0467	0.6066	0.8248	0.9767	0.7607	59.9044	15.4770	216.7641	0.7910	0.0472	0.1896	0.7172	0.6982	2.65
19	150	0.15	1.2	0.110	60.7828	0.1147	0.6783	1.7692	0.1139	0.5738	0.8667	0.9432	0.7396	60.6078	15.5772	219.3943	0.7854	0.1147	0.3563	0.5109	0.5235	2.47
20	150	0.20	1.2	0.110	60.7310	0.0251	0.9608	14.0105	0.0221	0.7090	0.6554	0.9894	0.8355	60.4746	15.5466	223.5878	0.6357	0.0251	0.1058	0.6822	0.6973	2.21
21	150	0.25	1.2	0.110	61.6709	0.0744	0.7551	2.7028	0.0728	0.6920	0.6839	0.9639	0.8246	61.4619	15.6916	227.3734	0.6303	0.0744	0.2631	0.7491	0.7281	2.80
22	175	0.15	1.2	0.115	59.4615	0.1374	0.6814	1.2973	0.1371	0.4652	1.0132	0.9315	0.6372	59.2769	15.4032	210.5579	0.9176	0.1374	0.4003	0.4307	0.4509	4.69
23	175	0.20	1.2	0.150	59.6530	0.1500	0.6700	2.1184	0.1475	0.4798	1.0435	0.9266	0.6585	59.4699	15.4273	210.7338	0.9368	0.1500	0.4233	1.1371	1.0996	3.30
24	175	0.25	1.2	0.110	60.4652	0.0283	0.9615	18.7142	0.0259	0.6952	0.7019	0.9874	0.8274	60.2151	15.5063	221.2560	0.6802	0.0283	0.1207	0.9007	0.8677	3.66
25	200	0.15	1.2	0.080	62.7618	0.0273	0.8235	0.8415	0.0232	0.8304	0.3767	0.9890	0.9085	62.5077	15.8365	239.9516	0.3552	0.0273	0.1095	0.5133	0.4962	3.33
26	200	0.20	1.2	0.115	60.6591	0.0206	0.9691	18.0500	0.0204	0.6988	0.6747	0.9898	0.8287	60.4002	15.5353	222.5755	0.6604	0.0206	0.0999	1.3305	1.2985	2.41
27	200	0.25	1.2	0.115	61.2520	0.0146	0.9653	5.9800	0.0143	0.7191	0.5781	0.9929	0.8384	60.9991	15.6269	227.6032	0.5677	0.0146	0.0752	1.3852	1.3342	3.68

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Table 10 Input parameters considered for RBFNN model 1 (speed rate, feed rate, depth of cut, tool flank wear, and 15 GLCM features) for surface roughness prediction and comparison of R_a for stylus measured and predicted values along with errors obtained (randomly selected data).

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