Fig 1.
Genetic algorithm flowchart.
Table 1.
Details of unimodal test functions.
Table 2.
Details of multi-modal test functions.
Table 3.
Details of fixed-dimension test functions.
Fig 2.
(a) Mutation rate. (b) Population size. (c) Max iteration.
Table 4.
The parameter settings.
Fig 3.
Qualitative results for the F12 function.
(a) Parameter space. (b) Population distribution. (c) Best record. (d) Convergence curve.
Fig 4.
Qualitative results for the F13 function.
(a) Parameter space. (b) Population distribution. (c) Best record. (d) Convergence curve.
Fig 5.
Qualitative results for the F14 function.
(a) Parameter space. (b) Population distribution. (c) Best record. (d) Convergence curve.
Fig 6.
Qualitative results for the F15 function.
(a) Parameter space. (b) Population distribution. (c) Best record. (d) Convergence curve.
Table 5.
Results of test functions (F1-F11) with 30 dimensions.
Table 6.
Results of test functions (F1-F11) with 50 dimensions.
Table 7.
Results of test functions (F1-F11) with 100 dimensions.
Table 8.
Results of test functions (F12–15) with fixed dimensions.
Fig 7.
The model of network adversarial attack.
(a) The structure of DCNN for experiment. (b) The model of network adversarial attack.
Fig 8.
The confidence change of the binary image after iteration.
Fig 9.
Statistical table of experimental results.
Fig 10.
The confidence curve of a binary image.