Research on Generative AI-Based Architectural Design and Style Reconstruction Technology - Wu, Chongyan (2025 IEEE 3rd International Conference on Image Processing and Computer Applications (ICIPCA), 2025)
This research examines the generative artificial intelligence's (AI) application systems on the analysis and reconstruction of architectural styles through the cultural integrity preservation lenses and design modification encouragement. The study constructs a framework for AI comprising feature extraction of architecture, semantic analysis and deep learning style diffusion reconstruction. The framework integrates historical and cultural contexts to evaluate architectural styles in three basic features domains: Assuming a multi-dimensional representation system of features architectural styles as developed structures assists in comprehension of the interrelations between architectural features. The research proposes and applies a new approach to semantic analysis directed towards understanding the construct description of an architectural style from a historical design preservation with a contemporary vision reinterpretation approach. The effectiveness of the framework is validated through case study investigations, comparative performance analysis, and expert appraisal, which attest to changes in style recognition up to 92.5% and design flexibility. Findings also prove that the AI digital tools design and modernisation integration with traditional architecture knowledge and skills facilitates the architectural heritage preservation while providing innovative design approaches. This work constitutes a remarkable achievement of artificial intelligence in the application of architectural design and provides a foundation to reconcile against the principles of heritage conservation and modern architecture.