2019 VOL.2 Aug No.4

• Title: Research on Physical Fitness Grading Model of Swimming Training Based on Real-time Cloud Computing
• Name: Broderick Douglas
• Company: The University of Nottingham, Malaysia Campus
• Abstract:

  When the traditional physical fitness grading model is used to classify the swimming training physical fitness, there are cases where the classification accuracy is low and the stability is poor. Aiming at the above problems, a fitness training grading model based on real-time cloud computing is proposed. Firstly, the cloud computing is used to select the hierarchical indicators constructed by the model and assign weights to them. Then, the comment set is established. At the same time, according to each index, the weighting value is used to determine the rating scale of the index, and the membership matrix is constructed on this basis. Realize fuzzy comprehensive evaluation of physical fitness, and finally determine the level of comments against the scale of comments. The results show that compared with the traditional physical fitness classification model, the classification accuracy is improved by 20%, and the accuracy of the model does not decrease with the increase of the number of classifications, and the stability is better.

• Keyword: Cloud Computing; Swimming Training Physical Fitness; Physical Fitness Grading; Hierarchical Model;
• DOI: 10.12250/jpciams2019040129
• Citation form: Broderick Douglas.Research on Physical Fitness Grading Model of Swimming Training Based on Real-time Cloud Computing[J]. Computer Informatization and Mechanical System, 2019, vol. 2, pp. 16-21.

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