2022
DOI: 10.1155/2022/5872384
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Prediction of College Students’ Sports Performance Based on Improved BP Neural Network

Abstract: Sports performance prediction has gradually become a research hotspot in various colleges and universities, and colleges and universities pay more and more attention to the development of college students’ comprehensive quality. Aiming at the problems of low accuracy and slow convergence of the existing college students’ sports performance prediction models, a method of college students’ sports performance prediction based on improved BP neural network is proposed. First, preprocess the student’s sports perfor… Show more

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Cited by 4 publications
(5 citation statements)
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“…The student's sports performance data enable the establishment of an ideal college student's sports performance prediction model by optimizing the choice of weights and thresholds in the neural network using the DE algorithm. According to Tang, et. al., (2022), the DE algorithm model may increase the reliability of prediction findings, enhance the accuracy of college students' sports performance prediction, and give useful information for sports training.…”
Section: Student Supportmentioning
confidence: 99%
“…The student's sports performance data enable the establishment of an ideal college student's sports performance prediction model by optimizing the choice of weights and thresholds in the neural network using the DE algorithm. According to Tang, et. al., (2022), the DE algorithm model may increase the reliability of prediction findings, enhance the accuracy of college students' sports performance prediction, and give useful information for sports training.…”
Section: Student Supportmentioning
confidence: 99%
“…In this paper, the error reverse propagation neural network prediction model, which is proposed by Zhang (2019), is used. This model is based on machine learning algorithm, and includes input layer, implied layer, output layer and transfer function between layers.…”
Section: Neural Network With Reverse Propagation Of Errormentioning
confidence: 99%
“…Literature [1] expounds the in uence of extracurricular sports on academic achievements. References [2,3], respectively, use particle swarm optimization and PSO-SVM learning methods to predict sports performance. Literature [4] proposes a sports performance prediction algorithm combining gray prediction features with CNNs and optimizes the sports competition performance prediction model of extreme learning machine based on the Drosophila algorithm in literature [5], so that the performance prediction can achieve higher prediction accuracy and computational e ciency.…”
Section: Introductionmentioning
confidence: 99%