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Table 5 Performance of classical vs multi objective real-coded GA over 20 runs using the 2-gene synthetic dataset

From: Comparison of evolutionary algorithms in gene regulatory network model inference

Criteria CLGA MOGA Fuzzy MOGA
Goodness of data fit (Best/Average SE) 0.04115/0.209183826 0.023202753/0.14008799 0.019817555/0.10705668
Parameter quality (Best/Average SE) 2.368969422/10.25508788 1.138802292/11.22558038 1.685895101/9.676239684
Robustness (Kinetic orders/Rate constants variance) 0.324876643/1.107014477 0.320798581/4.085473222 0.279334243/1.518127766
Average running time 187.6s 302.8s 300.6s