Feature Extraction and Classification of Power Quality Disturbances Using Optimized Tunable-Q Wavelet Transform and Incremental Support Vector Machine

Table 5

Performance comparison of OTQWT-ISVM for different values of Q and r.

Classes	OTQWT-ISVM (with decomposition parameters, Q = 2.5 and r = 3)						OTQWT-ISVM (with decomposition parameters, Q = 3.5 and r = 3)
	Training time (s)	Testing time (s)	Training RMSE	Testing RMSE	Accuracy (%)		Training time (s)	Testing time (s)	Training RMSE	Testing RMSE	Accuracy (%)
					Noise free-case	20 dB					Noise free-case	20 dB
PCL1	0.0179	0.0130	0.0039	0.0122	100	100	0.0296	0.0197	0.0009	0.0057	100	100
PCL2	0.0158	0.0105	0.0061	0.0227	100	100	0.0275	0.0172	0.0031	0.0161	100	100
PCL3	0.0163	0.0145	0.0038	0.0429	100	98.57	0.0280	0.0212	0.0008	0.0361	100	98.57
PCL4	0.0160	0.0130	0.0041	0.1325	98.57	98.57	0.0277	0.0197	0.0011	0.1151	100	100
PCL5	0.0164	0.0108	0.0118	0.1812	100	100	0.0281	0.0175	0.0088	0.1707	98.57	100
PCL6	0.0177	0.0120	0.0072	0.1387	98.57	98.57	0.0294	0.0187	0.0042	0.1260	100	98.57
PCL7	0.0169	0.0133	0.0105	0.1843	100	100	0.0286	0.0199	0.0075	0.1736	100	100
PCL8	0.0166	0.0117	0.0162	0.3052	98.57	98.57	0.0283	0.0184	0.0132	0.2869	100	98.57
PCL9	0.0164	0.0139	0.0185	0.3015	100	100	0.0281	0.0206	0.0155	0.2887	98.57	100
PCL10	0.0183	0.0145	0.0131	0.0635	100	100	0.0299	0.0212	0.0101	0.0591	100	100
PCL11	0.0179	0.0120	0.0039	0.0118	98.57	98.57	0.0296	0.0187	0.0009	0.0056	98.57	98.57
PCL12	0.0185	0.0145	0.0079	0.1676	98.57	98.57	0.0302	0.0212	0.0049	0.1625	100	100
Mean	0.0170	0.0128	0.0089	0.1303	99.40	99.28	0.0287	0.0195	0.0059	0.1205	99.64	99.52