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基于高斯特征的足球教育环境与学生心理健康相关性分析。

Analysis of the Correlation between Football Education Environment and Students' Psychology Health Based on Gauss Characteristics.

机构信息

Liaoning Shihua University, Institute of Physical Education, Fushun 113001, China.

Institute of Physical Education, University of Huanggang Normal University, Huanggang 438000, China.

出版信息

J Environ Public Health. 2022 Sep 25;2022:9429846. doi: 10.1155/2022/9429846. eCollection 2022.

Abstract

Campus football has become a core content of school physical education. Through football education, we can cultivate students' sound personality and promote students' all-round physical and mental development. At the same time, through psychological skills training methods, we can enrich the educational methods of football skills and provide theoretical reference for promoting educational reform. On the basis of Gaussian features, this paper combines the mixed Gaussian feature model to further describe the relationship between football education and students' psychology. At the same time, Apriori association rule algorithm in data mining is introduced, and Apriori algorithm is improved in parallel with Hadoop data processing platform. Several parallel association rule algorithms are emphatically studied and analyzed to strengthen the analysis of the relationship between football education and students' psychology. The results show that the average recognition rate of the correlation between football education and students' psychology based on Gaussian features is 17.91% higher than that of ordinary results, which obviously improves the correlation recognition result and has a good descriptive ability. Therefore, it has become an important issue for today's physical education workers to analyze the correlation between football education and students' psychology in order to cultivate students' sports and mental health.

摘要

校园足球已成为学校体育教育的核心内容。通过足球教育,可以培养学生健全的人格,促进学生身心的全面发展。同时,通过心理技能训练方法,可以丰富足球技能的教育方法,为推动教育改革提供理论参考。本文在高斯特征的基础上,结合混合高斯特征模型,进一步描述足球教育与学生心理之间的关系。同时,引入数据挖掘中的 Apriori 关联规则算法,并在 Hadoop 数据处理平台上进行并行改进。重点研究和分析了几种并行关联规则算法,以加强对足球教育与学生心理关系的分析。结果表明,基于高斯特征的足球教育与学生心理相关性的平均识别率比普通结果高出 17.91%,明显提高了相关性识别结果,具有良好的描述能力。因此,分析足球教育与学生心理的相关性,培养学生的体育和心理健康,已成为当今体育工作者的重要课题。

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