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Research on Application of Sports Training Performance Prediction Based on Convolutional Neural Network
Author(s) -
Yunlong Li,
HaoZhen Zhao,
JiaYu Gao
Publication year - 2022
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2022/7295833
Subject(s) - convolutional neural network , computer science , training (meteorology) , weighting , artificial neural network , artificial intelligence , similarity (geometry) , machine learning , feature (linguistics) , point (geometry) , data mining , pattern recognition (psychology) , image (mathematics) , mathematics , medicine , linguistics , meteorology , geometry , philosophy , radiology , physics
In order to improve the prediction effect of sports training performance and improve the effect of sports training, this paper classifies the sports training image area, refines the image into different areas, finds suspicious areas, and completes the error prediction. Moreover, this paper calculates the regional similarity of sports training images in the fully connected layer of the convolutional neural network and introduces the local linear weighting method for analysis. In addition, this paper gives a certain weight to each prediction point near the area to be predicted and selects the suspicious area feature based on the multievaluation standard fusion method. Finally, this paper combines the convolutional neural network algorithm to construct a sports training performance prediction system to improve the effect of sports training and design experiments to verify the system proposed in this paper. From the experimental research results, we can see that the sports training performance prediction system based on the convolutional neural network proposed in this paper has good practical effects.

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