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Table 6 Validation of two subsidiary improvements and comparative experiments between GA and RBFN including above-mentioned improvements. The comparison between k NN and ADSGA are shown in the columns headed k NN and the second columns from right headed ADSGA. The results acquired with the conventional k NN method and our proposed ADSGA are shown in the columns headed k NN and ADSGA. The improved results obtained with the fitness transformation are demonstrated in the 2 columns headed ADSGA and ADSGA+Log. The validation of main improvement that is the application of RBFN is presented in the leftmost GA column and the rightmost ADSGA+Log column. The proposed method yielded equivalent or more accurate results compared to the parameters obtained with GA at half the calculation time and a 50% increase in the optimization success rate.

From: Parameter estimation for stiff equations of biosystems using radial basis function networks

 

GA

RBFN

  

k NN

ADSGA

ADSGA Log

  

k = 2

k = 4

k = 8

k = 16

  

Convergence rate (%)

60

90

88

92

90

86

90

Processing time (min)

273

163

188

170

157

167

130

Test error (%)

10.3 ± 2.5

12.9 ± 3.9

10.4 ± 2.0

11.0 ± 2.3

11.8 ± 3.4

9.3 ± 2.2

10.8 ± 2.1