Application Analysis of 5G Intelligent Communication Technologies in the Field of Sports Distance Education.


Journal

Computational intelligence and neuroscience
ISSN: 1687-5273
Titre abrégé: Comput Intell Neurosci
Pays: United States
ID NLM: 101279357

Informations de publication

Date de publication:
2022
Historique:
received: 25 02 2022
revised: 09 04 2022
accepted: 16 04 2022
entrez: 5 7 2022
pubmed: 6 7 2022
medline: 7 7 2022
Statut: epublish

Résumé

China has entered a new fifth-generation (5G) technological period, college students are relatively fast to absorb new things, and conventional teaching methods are incapable of properly stimulating students' interest in sporting activities. As a result, the 5G integrated teaching paradigm, which is based on communication technology, is an unavoidable reform of sports remote education. For a long time, technology and sports have been inextricably linked. However, new possibilities on the Internet are fast developing, resulting in massive volumes of data. In this paper, we propose a novel 5G framework for efficient sports distance education. Initially, the sports dataset is preprocessed using normalization, and the features are extracted using Principal Component Analysis (PCA). Following feature selection, a Hierarchical Multiscale Convolutional Neural Network (HM-CNN) is used to categorize and initialize the 5G utilizing the Enhanced Transfer Control Protocol (E-TCP) for efficient data transmission. The Elevated Ant Colony Optimization Algorithm improves the performance of the suggested system even more (EACO). The experimental results indicate that 5G integrated education reform based on communication technology may successfully enhance the number of college students' sports population.

Identifiants

pubmed: 35785093
doi: 10.1155/2022/2115041
pmc: PMC9242758
doi:

Types de publication

Journal Article Retracted Publication

Langues

eng

Sous-ensembles de citation

IM

Pagination

2115041

Commentaires et corrections

Type : RetractionIn

Informations de copyright

Copyright © 2022 Yuanfeng Zhang and Majed.

Déclaration de conflit d'intérêts

The authors declare that they have no conflicts of interest.

Auteurs

Yuanfeng Zhang (Y)

P. E. Scientific College, Harbin Normal University, Harbin, Heilongjiang, China.
Tripoli Sports University, Tripoli, Libya.

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Classifications MeSH