AIGC Intelligent Cultural and Creative Product Design Generation and User Preference Propagation Integrating GAN Algorithms

In the rapidly emerging technology of AIGC (Artificial Intelligence Generated Content) within the cultural and creative sectors, generated content continues to have serious gaps in the form of quality consistency, cultural adaptation, and user preference equivalence, especially in the area of attaining fined control over image details, cultural appropriateness, and style features. To solve this reason, this paper presents a perception-feedback system that combines artificial intelligence and the Internet of Things (IoT). It is a mechanism that connects user interaction data, environmental semantic cues and the content generation model in real-time to address the issues of "uncontrollable results of generation, hard to follow user preference and lack of incorporating cultural aspects in the current intelligent perception and control systems. The paper develops a closed-loop model that comprises an IoT perception layer, a user behavior acquisition module, an AIGC content generator, and a reinforcement learning feedback mechanism. When interacting with the customer, the IoT terminal captures fine details of user browsing break, pattern magnification and color preference changes. These micro-interactions that occur frequently in real time and are analyzed by the AI model are converted to quantifiable aesthetic features, cultural symbol weight, and style vectors. The generation network adapts the parameters of a fine-grained control, like pattern density, color contrast, and the ratio of cultural elements, based on feedback, and thus cultural and creative products can be optimized through iterative refinement to a high degree of accuracy. It has been experimentally demonstrated that the system enhances the refinement of content generation significantly: aesthetic score by 20.0, cultural fit by 23.3, index of innovation by 24.2, general quality by 22.6, and matching of the preferences of the users by 18.4. These findings confirm the efficiency of the AI-IoT integration mechanism in AIGC cultural and creative products as one of the technological directions towards the fulfillment of intelligent generation delivering high quality, personalization, and cultural richness.