Table 5 Comparison results between EQPSO-2M and other algorithms
From: A high accuracy modeling scheme for dynamic systems: spacecraft reaction wheel model
Algorithm | Minimum best fitness | Maximum best fitness | Mean best fitness | STD | Success rate, % |
|---|---|---|---|---|---|
TAPSO | 6.7E−07 | 0.3229 | 4.4E−06 | 6.1E−06 | 63.3 |
PSO-In | 6.5E−07 | 0.4624 | 3.9E−06 | 6.4E−06 | 73.3 |
MPSO | 6.6E−07 | 0.6003 | 1.0E−05 | 4.8E−06 | 13.3 |
AGPSO | 6.7E−07 | 0.4677 | 8.4E−06 | 3.9E−06 | 20 |
ELPSO | 7.0E−07 | 0.1998 | 1.1E−05 | 5.8E−06 | 13.1 |
QPSO | 6.6E−07 | 0.3977 | 6.2E−06 | 6.5E−06 | 43.3 |
EQPSO-1M | 6.5E−07 | 0.0393 | 3.2E−06 | 1.8E−06 | 86.7 |
EQPSO-2M | 6.5E−07 | 0.0088 | 6.9E−07 | 1.6E−07 | 96.7 |