Research on Indoor Environment Art Design Model Using Genetic Algorithm
Algorithm 1GA-CNN algorithm
Viegin
Step 1 The data is processed in a standardized manner and divided into training sets, evaluation sets and test sets
Step 2 Initialize the population of the CNN framework structure, preset the maximum number of iterations G, and the current population algebra = 1;
Step 3 Learn to train each frame structure in the CNN population;
Step 4 Evaluate the trained CNN model with the evaluation set to obtain the corresponding adaptability of the CNN framework structure population
Step 5 Use the roulette method to generate mating targets;
Step 6 Crossover the mating target and perform training to assess fitness;
Step 7 Use the variation operation to mutate the crossover results and perform training to assess fitness;
Step 8 Determine whether the newly generated results are better than the mating target, update the CNN structure population, and update the corresponding adaptability
Step 9 If < G and the convergence condition is not met, = + 1, go to step 5, otherwise go to step 10;
Step 10 Output the elite individual model as the final classification model.
