Qiang Zhang1 and Jing Hu2This email address is being protected from spambots. You need JavaScript enabled to view it.
1School of Art, Anhui Jianzhu University Anhui Hefei, 230022, China
2School of Art Design, Anhui Wenda University of Information Engineering, Anhui Hefei, 230022, China
Received: November 20, 2025 Accepted: January 5, 2026 Publication Date: February 14, 2026
Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.
Modern architectural design is becoming data-driven, sustainable, and culturally adaptive through intelligent sensing, IoT, and algorithmic frameworks. This paper introduces a methodology combining clustering opti mization, deep generative modelling, and parametric reconstruction to digitize traditional Chinese architecture and design modern green buildings. Using StructGAN, neural simulations, and reinforcement learning, the system reconstructs heritage forms, optimizes structures, and monitors energy patterns. Results show high design fidelity, efficiency, and cultural coherence, bridging tradition with modernity.
Keywords: space aesthetics; Chinese architectural elements; Modern architectural design; Optimization of clustering algorithm
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