A Novel Optimization Approach for Revolutionizing Architectural Design in Chinese Cultural Heritage

A novel approach combining machine learning and augmented reality (AR) significantly enhances the accuracy of defect identification in Chinese cultural heritage architecture, achieving an F1 score of 95.47% and an accuracy of 93.29%. The study leverages an Ensemble Ant Colony Fused Convolutional Capsule Neural Network (EAC-CCNN) to analyze high-resolution images of structures like the Dazu Rock Carvings, Nanchan Temple, and Foguang Temple. By integrating this model with Building Information Modeling (BIM), researchers developed a safety management system that improves defect detection, promotes collaboration, and aids in the preservation of cultural heritage assets. The approach demonstrates potential for training machine learning models to recognize patterns, correct errors, and make informed predictions under varying conditions.

Li, X., & Yang, X. (2025). A Novel Optimization Approach for Revolutionizing Architectural Design in Chinese Cultural Heritage. HighTech and Innovation Journal, 6(1), 151–164. https://doi.org/10.28991/hij-2025-06-01-011