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Table 3 Results on RMSE and RMSEm of the models estimated from artificial data.

From: Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

Noise Scenario RMSE RMSEm
   DASA PSO DE A717 DASA PSO DE A717
  CO 0.0651 0.0527 0.0189 0.7005 0.0651 0.0527 0.0189 0.7005
0% AO 0.0625 0.0539 0.0250 0.6099 1.6272 0.7866 1.7876 1.0684
  TO 0.0951 0.1507 0.0197 0.6612 0.5857 0.4606 0.2511 0.7960
  NPO 0.2993 0.5040 0.2282 0.6881 2.6840 2.0717 3.9246 3.0273
  CO 0.1164 0.1121 0.0999 0.7287 0.1164 0.1121 0.0999 0.7287
5% AO 0.0902 0.0861 0.0690 0.6232 1.0437 0.9043 1.4639 1.3442
  TO 0.1363 0.1341 0.1006 0.6546 0.6162 0.2750 0.2831 0.9265
  NPO 0.3162 0.5166 0.2463 0.6897 2.8668 3.8831 6.6315 2.1172
  CO 0.3958 0.3941 0.3907 0.8113 0.3958 0.3941 0.3907 0.8113
20% AO 0.2770 0.2760 0.2707 0.6782 1.7547 1.0050 2.8513 1.3052
  TO 0.4023 0.3983 0.3917 0.7810 0.6967 0.4606 0.4289 0.9952
  NPO 0.4929 0.6407 0.4585 0.8023 2.1250 2.5423 2.8333 2.1999
  1. The table presents the median values of RMSE and RMSEm (over the 25 runs) of the models reconstructed with the parameters' estimates obtained by the three optimization methods from artificial data. The best values for both metrics are given in bold.