Research Article
Multiobjective Genetic Algorithm and Convolutional Neural Network Based COVID-19 Identification in Chest X-Ray Images
Algorithm 3
Hyperparameter tuning of CNN using multiobjective genetic algorithm.
| output: optimized population | | input: {Fitness function, demand, crossover_ratio} | | begin | (1) | Generate the random ; / represents the initial population /; | (2) | Calculate the fitness of ; | (3) | Sort ; | (4) | / Selection / | (5) | set = ; / denotes final population / | (6) | while ordo | (7) | / and represent children elimination and last generation / | (8) | Generate random ; / denotes children / | (9) set ; | (10) | for eachdo | (11) | Compute the fitness of ; | (12) | ifthen | (13) | remove ; | (14) | set ; | (15) | else | (16) | set = ; | (17) | end | (18) | end | (19) | / Mutation / | (20) | for crossover do | (21) | select and randomly; / , , and are children / | (22) | ; | (23) | Evaluate the fitness of ; | (24) | ifthen | (25) | remove ; | (26) | else | (27) | remove ; | (28) | end | (29) | end | (30) | next generation | (31) | end | (32) | / Ranking / sort the ; | (33) | return / returns the most dominant solution w.r.t. fitness function / | | end |
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