Table 2 The parameters applied with the corresponding used values.
From: An AI-based automatic leukemia classification system utilizing dimensional Archimedes optimization
Parameter | Description | Algorithm | Applied value |
|---|---|---|---|
N | No. of features | – | 34 |
\(T_{\max }\) | Maximum number of iterations | 30 | |
\(x\) | Constant | – | 0.99 |
\(y\) | 0.01 | ||
a | Control parameter | for GWO, SCA, and WOA | Linearly decrease from 2 to 0 over repetitions |
r1, r2 | Random vectors | for GWO | r1, r2 \(\in\) [0,1] |
c1, c2, c3 | Random Values | for SSA | c1, c2, c3 \(\in\) [0,1] |
\(\tau\) o | Initial Pheromone for each state for ACO | For ACO | 0.2 |
ρ | Evaporation rate | 0.2 | |
α | The relative importance of the pheromone value | 2 | |
β | The relative importance of the heuristic information | 1 | |
\({a}_{1}\) | Constant | For HHO | \({a}_{1}, {a}_{2}, {a}_{3}, {a}_{4}, p\) \(\in\) [0,1] |
\({a}_{2}\) | |||
\({a}_{3}\) | |||
\({a}_{4}\) | |||
\(p\) | |||
\({C}_{1}\) | Constant | For DAOA, AOA | 2 |
\({C}_{2}\) | 6 |
