Algorithm 1: Pseudocode of Grey Wolf Algorithm

# Grey Wolf algorithm parameter initialization 1. population_size = 20 2. max_iterations = 15 3. lower_bound = [8, 10−4, 100, 16] 4. upper_bound = [200, 5 × 10−, 600, 128] # Grey Wolf algorithm population initialization 5. population = initialize_population(population_size, lower_bound, upper_bound) # Iteratively search for the optimal solution 6. for iteration in range(max_iterations): 7.        fitness = evaluate_fitness(population) # Calculate the fitness value 8.        update_positions(population, fitness) # Update wolf pack position 9. best_solution = get_best_solution(population) # Get the optimal solution # Output the hyperparameters of the optimal solution 10. best_hyperparameters = decode_parameters(best_solution)