Table 1 Comparison of optimization methods used in past studies on MIM and similar optical sensors.
Study | Size (nm×nm) | Sensitivity | Optimization method | Pros | Cons |
|---|---|---|---|---|---|
750 × 1200 | 1240 (nm/RIU) | Manual tuning | Simple implementation | Time-consuming, local optima | |
450 × 850 | – | artificial neural network | fast, global optimization | slow convergence | |
400 × 960 | 1960 (nm/RIU) | Parametric sweep | Effective for small problems | Inefficient for large parameter spaces | |
450 × 600 | 2587.87 (nm/RIU) | Artificial neural network | Fast, global optimization | Limited application to MIM sensors | |
1200 × 800 | 1900 (nm/RIU) | GA | Global search capability | Slow convergence | |
1100 × 1000 | 137.4 (°/RIU) | PSO | Fast convergence | Limited application to MIM sensors | |
670 × 1000 | 2473 (nm/RIU) | Manual tuning | Wide application | Time-consuming, local optima |
