Mathematical Problems in Engineering / 2018 / Article / Tab 12

Research Article

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

Table 12

Comparison results of the selected different overlap factor for our approach are shown for Example 4, 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 =296, =2.8RMSERMSEL-T
(Training)(Testing)(second)

=4

1621971941600.22360.44290.2969

1551901901610.28010.23740.3438

1961911631480.28830.20040.3750

1461621961760.25630.32820.2656

1971621601940.22360.44290.3125

0.25440.33041.5938

The total training data points =296, =3.5RMSERMSEL-T
(Training)(Testing)(second)

=4

2081932192170.21510.43810.4219

2152131972000.26370.27280.3125

2182222001920.27610.20660.3906

1961832182050.24650.34370.3438

2272192081930.21510.43810.2969

0.24330.33991.7747

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