Table 2 Comparison of the performance of PCOBA and other evolutionary algorithms.
Datasets | Algorithms | Avg. Fitness | Avg. Residue | Avg. Variance | Avg. Volume |
|---|---|---|---|---|---|
E a | GA | 11.96 ± 16.32 | 203.51 ± 323.67 | 19745 ± 9587.70 | 105.28 ± 54.28 |
|  | CGA | 3.90 ± 6.99 | 36.63 ± 140.32 | 21220 ± 7202 | 72.39 ± 20.11 |
|  | EDA | 5.80 ± 11.14 | 81.84 ± 220.84 | 23527 ± 6719.4 | 127.48 ± 21.64 |
|  | PCOBA | 1.88 ± 0.06 | 0.05 ± 0.00 | 26254 ± 833.22 | 104.90 ± 8.49 |
E b | GA | 5.59 ± 10.16 | 76.67 ± 201.51 | 18570 ± 7496.3 | 107.17 ± 38.87 |
|  | CGA | 3.05 ± 5.02 | 20.03 ± 100.81 | 22489 ± 6876.7 | 75.49 ± 18.99 |
|  | EDA | 5.12 ± 8.28 | 67.63 ± 163.60 | 20862 ± 6834.7 | 112.36 ± 44.52 |
|  | PCOBA | 2.03 ± 1.35 | 2.74 ± 26.88 | 25199 ± 3295.9 | 99.66 ± 16.92 |
E c | GA | 2.21 ± 0.02 | 262.63 ± 9.05 | 3807.20 ± 1068 | 470.96 ± 18.90 |
|  | CGA | 2.20 ± 0.03 | 263.09 ± 7.55 | 3229.40 ± 1160.4 | 443.00 ± 19.07 |
|  | EDA | 2.22 ± 0.05 | 263.94 ± 6.96 | 2359.70 ± 228.74 | 450.83 ± 50.57 |
|  | PCOBA | 1.94 ± 0.05 | 265.01 ± 4.63 | 2473.50 ± 176.1 | 562.63 ± 47.43 |