Mathematical Problems in Engineering / 2018 / Article / Tab 1

Research Article

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

Table 1

Comparison results of the proposed method, [15], G-LSSVR and Local-LSSVR with the hyper-parameter set , and the overlap factor as 1.5 are shown for Example 1.

: the number of the SRMs RMSE (Training)RMSE (Testing)
our approach[15]our approach[15]

3-SRMs0.21720.81840.21510.8186

5-SRMS0.03680.54460.03630.5447

7-SRMs0.01460.35540.01400.3556

9-SRMs0.00790.33890.00760.3391

12-SRMS0.00420.19570.00400.1961

15-SRMs0.00260.14710.00260.1472

G-LSSVR1.72951.7298

Local-LSSVR

M=21 training points3.76353.7630

M=41 training points1.17421.1622

M=61 training points0.00540.0050

M=81 training points0.00280.0026

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