TY - JOUR
AU - Xin Li
AU - Jing Yang
AU - Hongrun Shao
AU - Wenjing Liu
AU - Guoxin Li
AB - This study focuses on the integration of artificial intelligence and computer-aided design (CAD) in preserving and teaching Hebei s intangible cultural heritage, in particular, folk dance. It uses neural network algorithms to analyze audience engagement with Hebei s dance culture, using natural language processing to assess public response and emotional connections through big data. It also explores how CAD technology can create interactive, 3D-based teaching tools, including flipped classrooms and instructional dance videos. The findings demonstrate that neural network-driven audience analysis yields accurate insights into public interest, and CAD-enhanced teaching methods significantly improve learning efficiency and cultural preservation efforts. This study offers an innovative approach to combining artificial intelligence, cultural heritage, and education.
DO - 10.4018/IJCINI.383059
M1 - 1
N2 - This study focuses on the integration of artificial intelligence and computer-aided design (CAD) in preserving and teaching Hebei s intangible cultural heritage, in particular, folk dance. It uses neural network algorithms to analyze audience engagement with Hebei s dance culture, using natural language processing to assess public response and emotional connections through big data. It also explores how CAD technology can create interactive, 3D-based teaching tools, including flipped classrooms and instructional dance videos. The findings demonstrate that neural network-driven audience analysis yields accurate insights into public interest, and CAD-enhanced teaching methods significantly improve learning efficiency and cultural preservation efforts. This study offers an innovative approach to combining artificial intelligence, cultural heritage, and education.
TI - Neural Network Audience Analysis and CAD-Based Teaching for Intangible Cultural Heritage Dance
VL - 19
SN - 1557-3958
ER -