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Table 3 Performance comparison of four algorithms

From: An image denoising method based on BP neural network optimized by improved whale optimization algorithm

F PSO GWO WOA MSWOA
Avg Std Avg Std Avg Std Avg Std
F1 0.000201 0.000358 9.8969e−28 1.7798e−27 1.3287e−71 4.6923e−71 2.987e−235 0.000000
F2 0.027834 0.022819 9.4228e−17 4.0359e−17 6.5191e−52 1.3916e−51 7.4087e−122 2.7436e−121
F3 3.2627 2.829 3.254 3.5172 2.537 2.8982 1.1964 0.60541
F4 1.0994 0.20903 6.1646e−07 5.0583e−07 43.683 30.5652 2.9716e−120 1.5375e−119
F5 82.3794 94.0824 27.9435 0.85738 27.996 0.53038 27.8959 0.1526
F6 9.3017e−05 0.000108 0.80641 0.41776 0.39688 0.23078 0.20277 0.065166
F7 0.17078 0.057366 0.002217 0.001334 0.003305 0.004761 8.907e−05 6.9351e−05
F8 56.481 15.5315 2.8209 3.4839 0.000000 0.000000 0.000000 0.000000
F9 0.009372 0.009238 0.002068 0.005518 0.011227 0.042789 0.000000 0.000000
F10 0.010368 0.041732 0.041238 0.016416 0.032643 0.044017 0.007025 0.002786
F11 0.39789 0.000000 0.39789 4.6716e−06 0.39789 8.4987e−06 0.39878 0.003067
F12 \(-8.5514\) 3.1639 \(-10.4012\) 0.000910 \(-7.8285\) 2.963 \(-8.0695\) 2.3667