Aesthetic Value Evaluation for Digital Cultural and Creative Products with Artificial Intelligence

The domestic cultural and creative industry has abundant resource advantages broad development space. design for products evolved rapidly with the objective to improve its quality. industries have seen rapid growth in recent years wherein digital technologies been incorporated traditional methodologies. aspect acts are extremely important dissemination of culture on network platform. This is also supported by state vigorously implement innovative industrial policies. However, adoption technology a novel approach. But there exists lack understanding terms nature protocols. It thus necessary study relevant theories guide industry. increasingly prosperous aesthetic culture, especially industries, comprehensively improved value products. Therefore, methods evaluate realize digital, cultural, present day age. In this study, neural used an back propagation (BP) order At outset, basic idea, structural characteristics, learning algorithm, flow functioning BP analyzed. Then, evaluation model developed. Next, considering shortcomings network, segmentation adaptive strategy view field step size artificial fish swarm algorithm (AFSA). Finally, improvised verified simulation results reveal improvement convergence speed as well optimal solution accuracy part