Modeling of Sports Performance Based on Nonlinear Screening Factors and Weighting to Improve Prediction Accuracy

Author(s):  
Zhang Fan
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Xin Liu ◽  
Alaa Omar Khadidos ◽  
Mohammed Yousuf Abo Keir

Abstract Aiming to solve the problems in the traditional multiple regression analysis model for predicting college sports performance based on the principles of econometrics, a predictive model that combines genetic algorithm (GA), college sports performance evaluation and regression analysis is proposed. GA is used to conduct dynamic and supervised optimisation evaluation of college sports performance; on this basis, combined with regression analysis and GA's global optimisation capabilities, a complex nonlinear relationship between student sports performance and influencing factors is established; the student's performance is calculated based on the college sports performance. The results show that the method has high prediction accuracy and good stability.


2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Sitong Yang ◽  
Lina Luo ◽  
Baohua Tan

Artificial neural network has the advantages of self-training and fault tolerance, while BP neural network has simple learning algorithms and powerful learning capabilities. The BP neural network algorithm has been widely used in practice. This paper conducts research on sports performance prediction based on 5G and artificial neural network algorithms. This paper uses the BP neural network algorithm as a pretest modelling method to predict the results of the 30th Olympic Men’s 100m Track and Field Championships and is supported by the MATLAB neural network toolbox. According to the experimental results, the scheme proposed in this paper has better performance than the other prediction strategies. In order to explore the feasibility and application of the BP neural network in this kind of prediction, there is a lot of work to be done. The model has a high prediction accuracy and provides a new method for the prediction of sports performance. The results show that the BP neural network algorithm can be used to predict sports performance, with high prediction accuracy and strong generalization ability.


2008 ◽  
Vol 44 ◽  
pp. 63-84 ◽  
Author(s):  
Chris E. Cooper

Optimum performance in aerobic sports performance requires an efficient delivery to, and consumption of, oxygen by the exercising muscle. It is probable that maximal oxygen uptake in the athlete is multifactorial, being shared between cardiac output, blood oxygen content, muscle blood flow, oxygen diffusion from the blood to the cell and mitochondrial content. Of these, raising the blood oxygen content by raising the haematocrit is the simplest acute method to increase oxygen delivery and improve sport performance. Legal means of raising haematocrit include altitude training and hypoxic tents. Illegal means include blood doping and the administration of EPO (erythropoietin). The ability to make EPO by genetic means has resulted in an increase in its availability and use, although it is probable that recent testing methods may have had some impact. Less widely used illegal methods include the use of artificial blood oxygen carriers (the so-called ‘blood substitutes’). In principle these molecules could enhance aerobic sports performance; however, they would be readily detectable in urine and blood tests. An alternative to increasing the blood oxygen content is to increase the amount of oxygen that haemoglobin can deliver. It is possible to do this by using compounds that right-shift the haemoglobin dissociation curve (e.g. RSR13). There is a compromise between improving oxygen delivery at the muscle and losing oxygen uptake at the lung and it is unclear whether these reagents would enhance the performance of elite athletes. However, given the proven success of blood doping and EPO, attempts to manipulate these pathways are likely to lead to an ongoing battle between the athlete and the drug testers.


2009 ◽  
Author(s):  
Benjamin Scheibehenne ◽  
Andreas Wilke ◽  
Peter M. Todd
Keyword(s):  

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