Data Analysis of Related Factors of Adolescent Physical Exercise Behavior Based upon Artificial Neural Network Model

Author:

Chen Zhiling1ORCID,Dai Xinghong2ORCID,Ren Lili3

Affiliation:

1. School of Physical Education, University of South China, Hengyang, 421001 Hunan, China

2. School of Physical Education, Hunan University, Changsha, 410082 Hunan, China

3. School of Architecture and Design Arts, University of South China, Hengyang, 421001 Hunan, China

Abstract

Physical exercise behavior is to protect physical health through scientific physical activity (certain frequency, time, and intensity) in leisure time. The purpose of this paper is to study how to analyze and study the related factors of adolescent physical exercise behavior based on an artificial neural network model and describe the BP learning algorithm. This paper raises the question of the influencing factors of adolescents’ physical exercise behavior. This problem is based on an artificial neural network, so the paper expounds around the concept of artificial neural network and related algorithms and designs and analyzes relevant factors. The experimental results show that among the 4-17-year-old respondents, 45 students have the habit of physical exercise, accounting for 37.5% of the respondents in this age group. Among the 59 people with the habit of physical exercise in this survey, 41 people, accounting for 69.5%, believed that their interest in sports was greatly influenced by their surrounding classmates. There are 40 parents who have one parent who is college or above, accounting for 67.8% and other data. All of them show that the influencing factors of adolescents’ physical exercise behavior come from many aspects.

Funder

Education Department of Hunan Province

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3