@article{11313,
  author = {Xin Li and Jing Yang and Hongrun Shao and Wenjing Liu and Guoxin Li},
  title = {Neural Network Audience Analysis and CAD-Based Teaching for Intangible Cultural Heritage Dance},
  abstract = {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.},
  volume = {19},
  number = {1},
  issn = {1557-3958},
  doi = {10.4018/IJCINI.383059},
}