The expression method of Chinese creative elements in animation films based on artificial intelligence technology

This study explores the application of artificial intelligence to enhance the representation and evaluation of Chinese cultural elements in animated films, emphasizing both cultural significance and market potential while redefining intellectual property (IP) value in the industry. A major challenge addressed is the accurate assessment of cultural content, as traditional Back Propagation Neural Networks (BPNNs) often suffer from slow convergence and local minima issues. To overcome these limitations, the research proposes an improved GA-BP model, combining BPNN’s localized optimization with the global search capabilities of Genetic Algorithms (GA). The paper reviews cultural development theories and examines the status of Chinese and international animation IPs. Experimental results show that the GA-BP model achieves higher accuracy and stability than standard BPNNs, closely matching expert evaluations. This validates its effectiveness in supporting intelligent cultural evaluation and creative design in animation. By applying AI techniques to cultural evaluation, the research applies artificial intelligence methods to evaluate and support the structured integration of cultural elements into animated film design, laying a methodological groundwork for innovation in Chinese animated films. It supports cultural sustainability and strengthens national cultural identity through digital storytelling, contributing to both academic inquiry and industry practice.