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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