Fuzzy Weighted Least Squares Support Vector Regression with Data Reduction for Nonlinear System Modeling

Table 9

Comparison results of the selected different overlap factor for our approach are shown for Example 3, where represents the number of SRMs, L-T the computational time for constructing all SRMs, and the number of data points for each training subset.

The total training data points =501								RMSE	RMSE	L-T
=5								(Training)	(Testing)	(second)
=1.1	106	106	118	118	117	–	–	0.2531	0.0142	0.2813
=2.5	268	183	266	183	267	–	–	0.2756	0.2881	0.3438
=7
=1.1	83	99	98	97	98	98	83	0.2287	0.2537	0.2656
=2.5	222	147	147	215	222	221	215	0.2818	0.2894	0.4063