Skip to content
Publish & Distribute
Publishing Solutions
Distribution Solutions
Library Services
Subjects
Architecture and Design
Arts
Business and Economics
Chemistry
Classical and Ancient Near Eastern Studies
Computer Sciences
Cultural Studies
Engineering
General Interest
Geosciences
History
Industrial Chemistry
Jewish Studies
Law
Library and Information Science, Book Studies
Life Sciences
Linguistics and Semiotics
Literary Studies
Materials Sciences
Mathematics
Medicine
Music
Pharmacy
Philosophy
Physics
Social Sciences
Sports and Recreation
Theology and Religion
Publications
Journals
Books
Proceedings
Publishers
Journal Matcher
Blog
Contact
Search
English
English
Deutsch
Polski
Español
Français
Italiano
Cart
Home
Journals
Applied Mathematics and Nonlinear Sciences
Volume 10 (2025): Issue 1 (January 2025)
Open Access
Data-driven Optimization of Folk Dance Inheritance and Protection Strategies and Their Realization Paths
Wenjing Zhou
Wenjing Zhou
Dance Academy of Nanjing University of Arts
Nanjing, China
Search for this author on
Sciendo
|
Google Scholar
Zhou, Wenjing
Sep 26, 2025
Applied Mathematics and Nonlinear Sciences
Volume 10 (2025): Issue 1 (January 2025)
About this article
Previous Article
Next Article
Abstract
Article
Figures & Tables
References
Authors
Articles in this Issue
Preview
PDF
Cite
Share
Download Cover
Published Online:
Sep 26, 2025
Received:
Jan 12, 2025
Accepted:
Apr 27, 2025
DOI:
https://doi.org/10.2478/amns-2025-1056
Keywords
Gaussian model
,
Median filtering method
,
Multi-branch temporal features
,
Adaptive graph convolutional network (MTSGCN)
,
Folk dance
© 2025 Wenjing Zhou, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
