Combined digital media technology and advanced computing science in folk art design application

With the continuous development of intelligent computer technology, its application in the field of art and design is becoming increasingly widespread. However, the current application of artificial intelligence technology in folk art design is relatively simple and lacks systematic analysis methods. Therefore, this study aims to construct an optimization model through the use of advanced computational science methods and digital media technology to achieve a comprehensive analysis of various indicators of folk art design. This study uses watermark verification theory and digital models to analyze folk art design, and constructs corresponding optimization models through parameter encoded verification curves and calculations of different indicators. This model can conduct targeted analysis for different indicators to obtain corresponding calculation results. The experimental results show that the model calculation results exhibit relatively significant fluctuations in design concepts and public aesthetics, indicating that these two factors have a significant impact on the model. The design strategy presents a linear variation, with a relatively small range of changes in overall aesthetics and color elements, and a relatively small impact on the calculation results. In addition, the validation coefficient has an effect when the independent variable is small, while larger independent variables have an inhibitory effect on the validation coefficient. This study achieved a comprehensive analysis of various indicators of folk art design by constructing an optimization model. The effectiveness and accuracy of the model have been verified through comparison with experimental data.