Research Article
[Retracted] Gender-Based Deep Learning Firefly Optimization Method for Test Data Generation
Algorithm 1
The pseudo code of Gen-DLFA.
(1) | Initialize the parameters of algorithm; | (2) | Initialize firefly population randomly as in (1); | (3) | Calculate brightness of each firefly according to fitness function; | (4) | while (iterator < maxGen){ | (5) | for the male firefly : | (6) | for to | (7) | Select a female randomly from female subgroup | (8) | if is brighter than | (9) | move to as in (8); | (10) | update the position of | (11) | End if; | (12) | End for; | (13) | construct general center firefly of male subgroup as in (9); | (14) | conduct deep learning of general center firefly as in (10); | (15) | for the female firefly : | (16) | for to | (17) | if general center firefly is brighter than | (18) | move to general center according as in (11); | (19) | update the position of ; | (20) | else | (21) | conduct cauchy mutation of as in (12); | (22) | update the position of ; | (23) | End if; | (24) | End for; | (25) | rank the firefly population and find the best solution ; | (26) | for to k | (27) | implement chaotic search near to get | (28) | if ( is brighter than ) | (29) | ; | (30) | End if; | (31) | End for; | (32) | output the ; | (33) | iterator++; | (34) | End while; |
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