def run_msdp_train(moea, targets, predict_model): moea_name = dictionaries.get_moea_name(moea) predict_model_name = dictionaries.get_model_method_name(predict_model) targets_name = dictionaries.get_target_composition(targets) folder_name = 'multi-objective/' + predict_model_name + '/' + moea_name + '/' + targets_name l = -20 u = 20 helpers.training_record_for_msdp(save_folder=folder_name, target=targets, predict_model=predict_model, l=l, u=u, moea=moea)
def run_msdp_fpa_l1_nsga2_toZero_train(): save_file = '多目标优化_FPA+L1_nsga2_toZero' target = [0, 3] predict_model = 'linear' l = -20 u = 20 maxgen = 100 drawing = 0 moea = 3 helpers.training_record_for_msdp(save_file=save_file, target=target, predict_model=predict_model, l=l, u=u, moea=moea, drawing=drawing, maxgen=maxgen)
def run_msdp_fpa_aae_nonz_nsga2_DE_toZero_train(): save_file = '多目标优化_FPA+AAE+numofnonzero_nsga2_DE_toZero' target = [0, 1, 2] predict_model = 'linear' l = -20 u = 20 maxgen = 100 drawing = 0 moea = 4 helpers.training_record_for_msdp(save_file=save_file, target=target, predict_model=predict_model, l=l, u=u, moea=moea, drawing=drawing, maxgen=maxgen)
def run_msdp_FPA_L1_MSE_train(moea): target_name = 'FPA_L1_MSE' save_file = dictionaries.get_moea_name(moea) + '/' + target_name target = [0, 3, 4] predict_model = 'linear' l = -20 u = 20 maxgen = 100 drawing = 0 moea = moea helpers.training_record_for_msdp(save_file=save_file, target=target, predict_model=predict_model, l=l, u=u, moea=moea, drawing=drawing, maxgen=maxgen)