Research Article
A Feature Weighted Fuzzy Clustering Algorithm Based on Multistrategy Grey Wolf Optimization
Table 2
Parameter values for the comparative algorithms.
| | Algorithm | Parameter | Value |
| | PSO | Cognitive and social constant | (C1, C2) 2, 2 | | Inertia weight | Linear reduction from 0.9 to 0.1 | | Velocity limit | 10% of dimension range | | GWO | Convergence parameter (a) | Linear reduction from 2 to 0 | | HGSO | M1 | 0.1 | | M2 | 0.2 | | a | 1 | | β | 1 | | K | 1 | | AO | a | 0.1 | | δ | 0.1 | | AOA | a | 5 | | μ | 0.5 | | MRFO | S | 2 | | MSGWO | Convergence parameter (a) | Nonlinear reduction from 2 to 0 | | k | 1/3 |
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