Research on Innovative Design Methods of Footwear in the Context of Generative Artificial Intelligence

Abstract

To address the mismatch between complex development requirements and traditional design efficiency in the era of artificial intelligence, a footwear innovation design method based on generative artificial intelligence is proposed, using athletic footwear as a case study. Through human-machine collaborative analysis of category products and user demand surveys, a hierarchical model comprising 4 primary indicators and 17 secondary indicators is constructed. The weights of various elements are calculated, and consistency testing was refined to transform vague user demands into specific design prompts. Using generative artificial intelligence technology to assist in footwear innovative design, through the trend matching, adversarial training, parameter optimization, noise generation and other steps to complete the preliminary design proposal. This proposal was optimized and practiced on the modeling software platform to verify its feasibility. Finally, the design proposal was evaluated for comprehensive satisfaction from four dimensions: color attributes, style attributes, material attributes, and functional attributes. The results indicate that the paradigm, derived from this method, offers significant practical value and provides research insights and methodological guidance for footwear design