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Advances in Nano Research
  Volume 12, Number 3, March 2022 , pages 263-279
DOI: https://doi.org/10.12989/anr.2022.12.3.263
 


A hybrid evaluation of information entropy meta-heuristic model and unascertained measurement theory for tennis motion tracking
Yongfeng Zhong and Xiaojun Liang

 
Abstract
    In this research, the physical education training quality was investigated using the entropy model to compute variance associated with a random value (a strong tool). The entropy and undefined estimation principles are used to extract the greatest entropy of information dependent on the index system. In the study of tennis motion tracking from a dynamic viewpoint, such stages are utilized to improve the perception of the players' achievement (Lv et al. 2020). Six female tennis players served on the right side (50 cm from the T point). The initial flat serve from T point was the movement under consideration, and the entropy was utilized to weigh all indications. As a result, a multi-index measurement vector is stabilized, followed by the confidence level to determine the structural plane establishment range. As a result, the use of the unascertained measuring technique of information entropy showed an excellent approach to assessing athlete performance more accurately than traditional ways, enabling coaches and athletes to enhance their movements successfully.
 
Key Words
    hybrid evaluation; information entropy; tennis motion tracking; unascertained measurement theory
 
Address
Yongfeng Zhong: College of Physical Education, Changsha University, Changsha 410022, Hunan, China

Xiaojun Liang: College of Humanities, Zhaoqing Medical College, Zhaoqing 526020, Guangdong, China
 

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