Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 1


Published
on

May 23, 2023


Pages


DOI

Article

The Characteristics and Monitoring System of Athletes’ Physical Strength Training Based on Tunable Neuron Mathematical Model

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Authors

JinAn Li Affiliation:
China Three Gorges University, Yichang, 443002, China


Abstract

In this paper, an adjustable neural network model is developed to predict the physical training load of athletes. This paper takes 48 contestants as experimental subjects. Then the average speed prediction method, nonlinear regression model prediction method and neural network model prediction method model are established to predict the training load. This paper uses three different prediction models to compare the training results. The relative error rate calculated by the average rate prediction method is about 23%. The close error rate calculated by the linear regression method is about 32%. The relative error rate calculated by the adjustable neural network is around 8%. The e flexible neural network model has good prediction accuracy.


Keywords

Physical training, Tunable neuron mathematical model, Strength training, Optimal load, Prediction method


Citation

Li, J. (2023). The characteristics and monitoring system of athletes’ physical strength training based on tunable neuron mathematical model. Applied Mathematics and Nonlinear Sciences, 8(1). https://doi.org/10.2478/amns.2023.1.00025

Published by: Engineering Journals

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