@article{4323,
  author = {Ning Liu},
  title = {Analysis of the Feasibility and Inspiration of Ant Colony Algorithm in University Physical Education Teaching},
  journal = {Journal of Intelligent Computing},
  year = {2024},
  volume = {5},
  number = {4},
  doi = {https://doi.org/10.6025/jic/2024/15/4/149-155},
  url = {https://www.dline.info/jic/fulltext/v15n4/jicv15n4_5.pdf},
  abstract = {This paper introduces the application of the ant colony algorithm in university physical
education teaching (such as physical exercises). It also provides new ideas and
methods for optimizing the teaching mode through analysing its feasibility and
inspiration. The ant colony algorithm is an algorithm based on the behavior
characteristics of ants when searching for food, and it can be used to solve problems
in university physical education teaching, such as selecting sports projects and
evaluating students’ physical fitness. Its application can promote the informatization
development of university physical education teaching and provide new ideas and
methods for optimizing the teaching mode. Applying the ant colony algorithm brings
new inspiration to university physical education teaching, helping students choose
suitable sports projects and promoting the informatization development of university
physical education teaching.},
}