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Table 2
A comparison between BFO, PSO, GA, DE, and SA.
| Criteria | BFO | PSO | GA | DE | SA |
|---|---|---|---|---|---|
| Convergence speed | Moderate | Fast | Slow to moderate | Fast | Slow |
| Accuracy | High | Moderate | Moderate | High | Moderate |
| Robustness | High (Resistant to local minima) | Moderate (Prone to premature convergence) | Moderate (Depends on population size) | High (Good exploration-exploitation balance) | Low (Stochastic behavior affects stability) |
| Computational complexity | Moderate to High | Low | High | Moderate | Moderate |
| Exploration vs. Exploitation | Balanced | Good exploitation but weak exploration | More exploration than exploitation | Well-balanced | Highly stochastic, risk of poor exploitation |
| Handling of nonlinearities | Excellent | Moderate | Moderate | Good | Weak |
| Ability to escape local minima | Strong bacterial behavior prevents stagnation | Weak | Depends on mutation strategy | Strong (Adaptive mutation) | Weak (Prone to local minima) |
| Best suited for electrical machine parameter identification? | (Accurate and robust for nonlinear systems) | (Prone to local minima, less accurate) | (Slow convergence, needs large population) | (High computational cost) | (Unstable for complex systems) |
| References | [27–35] | ||||
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