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Research on a Mobile Prediction Platform for Dynamic Changes in Athletic Performance Based on Screening Factors

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Abstract

Most of the traditional athletic performance dynamic change prediction platforms use gray correlation and neural networks to establish prediction methods, and the prediction results are inaccurate and time-consuming. Therefore, the construction of a mobile prediction platform for dynamic changes in athletic performance based on screening factors is proposed to improve the accuracy of its prediction results and shorten the prediction time. On the basis of hardware, the main body of students is determined, the athletic performance data of students is collected by the physical education management system of colleges and universities, and the missing data is filled by the criterion function of K-average algorithm. The KNN algorithm is used to make decisions to obtain the most representative predictors of athletic performance data, and the characteristics of students' athletic performance are extracted. The effective factors are selected according to the tenfold cross-validation fold MSE minimum principle of SVM, and the mandatory screening based on SVM is used to assign weights to each reserved factor. According to the weighted result of the obtained factors, the influencing factors of athletic performance are analyzed, and the weighting process is completed for the factors, and the athletic performance prediction is realized by using support vector machine. In the platform established in this paper, the students' 1000-m running results are predicted. The simulation results show that, compared with the traditional platform, the constructed platform has higher prediction accuracy and takes less time.

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Authors and Affiliations

  1. College of Education and Sport Sciences, Yangtze University, Jinzhou, 434020, China

    De-kun Jiang

  2. School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, 632014, India

    Thippa Reddy Gadekallu

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  1. De-kun Jiang
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  2. Thippa Reddy Gadekallu
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Correspondence to Thippa Reddy Gadekallu.

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The authors have no relevant financial or non-financial interests to disclose. Dekun Jiang provided the algorithm and experimental results, wrote the manuscript, Thippa Reddy Gadekallu revised the paper, supervised and analyzed the experiment. We also declare that data availability and ethics approval is not applicable in this paper.

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Jiang, Dk., Gadekallu, T.R. Research on a Mobile Prediction Platform for Dynamic Changes in Athletic Performance Based on Screening Factors. Mobile Netw Appl 27, 2585–2595 (2022). https://doi.org/10.1007/s11036-022-02074-7

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