Research Article
A Feature Weighted Fuzzy Clustering Algorithm Based on Multistrategy Grey Wolf Optimization
Table 4
Comparison of optimization performance of different k values in MSGWO.
| | Function | k = 1/3 | k = 1/2 | k = 1 | k = 2 | k = 3 |
| | f1 | Ave | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | 4.39E-257 | | Std | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | | f2 | Ave | 0.00E+00 | 0.00E+00 | 3.89E-247 | 1.09E-165 | 1.76E-130 | | Std | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | 1.83E-130 | | f3 | Ave | 0.00E+00 | 0.00E+00 | 0.00E+00 | 2.09E-250 | 5.37E-188 | | Std | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | | f4 | Ave | 0.00E+00 | 0.00E+00 | 1.38E-234 | 1.78E-152 | 1.92E-117 | | Std | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | | f5 | Ave | 6.65E-05 | 7.12E-05 | 9.05E-05 | 1.23E-04 | 1.38E-04 | | Std | 5.51E-05 | 7.22E-05 | 7.84E-05 | 1.17E-04 | 1.12E-04 | | f6 | Ave | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | | Std | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | | f7 | Ave | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | | Std | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | | f8 | Ave | 8.88E-16 | 8.88E-16 | 8.88E-16 | 8.88E-16 | 8.88E-16 | | Std | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 | 0.00E+00 |
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