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An assisted teaching algorithm for basketball shooting based on object decomposition.
- Source :
- Soft Computing - A Fusion of Foundations, Methodologies & Applications; Oct2022, Vol. 26 Issue 20, p10871-10878, 8p
- Publication Year :
- 2022
-
Abstract
- Basketball is one of the three ball games, loved by all sports enthusiasts, and shooting is the most basic means of scoring. In order to improve the scoring rate of basketball shooting, the teaching objective program and method program are combined to form an efficient teaching algorithm with comprehensive characteristics, which can improve the effect of basketball shooting training. In this paper, we design reasonable auxiliary teaching methods for basketball shooting, so that students can improve their scoring rate in daily basketball training and reduce injury when improving shooting skills. Our evaluation suggests that increasing the emphasis on the training of core muscle group is beneficial to enhance the control of core muscle group of athletes and promote the improvement of their shooting percentage. For people, without the basis of foundation and has a certain movement intermittent time, longer training time while shorter core training time were observed. Moreover, for physical quality, excellent and experienced player should be aimed at training projects, which strictly controls the intermittent time, while fully stimulates the core muscles, in order to achieve the training targets and complete the training results. We conclude that it is feasible and effective to design an auxiliary teaching algorithm for basketball shooting on the basis of object decomposition program. Furthermore, the proposed algorithm is approximately 11.23% better than the other methods in terms of higher scores. [ABSTRACT FROM AUTHOR]
- Subjects :
- BASKETBALL
BALL games
BASKETBALL training
ALGORITHMS
TEACHING methods
Subjects
Details
- Language :
- English
- ISSN :
- 14327643
- Volume :
- 26
- Issue :
- 20
- Database :
- Complementary Index
- Journal :
- Soft Computing - A Fusion of Foundations, Methodologies & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 159264175
- Full Text :
- https://doi.org/10.1007/s00500-022-07086-9