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基于关联规则算法的篮球运动员体能特征及综合体能评价模型

Physical fitness characteristics and comprehensive physical fitness evaluation model of basketball players based on association rule algorithm.

作者信息

Ding Yongkang

机构信息

Police Department, Shanxi Police Academy, Taiyuan, Shanxi, China.

出版信息

PLoS One. 2025 Jul 29;20(7):e0325925. doi: 10.1371/journal.pone.0325925. eCollection 2025.

Abstract

Physical fitness refers to the health of all body functions, including cardiorespiratory endurance, muscle strength, flexibility, stamina, and body composition, which can help individuals effectively cope with daily activities and sports challenges. This paper explores the physical characteristics of basketball players, aiming to improve training effects through unique physical evaluation indicators and provide a theoretical framework for improving college basketball performance and training standards. The study adopted the Apriori association rule algorithm in data mining. First, the physical data of basketball players were collected and preprocessed. Then, frequent item sets were extracted through the association rule mining algorithm, association rules were generated, and the key factors affecting the physical performance of athletes were analyzed. The article's results revealed the potential relationship between different physical characteristics and emphasized the application prospects of association rule mining in the physical evaluation of basketball players.

摘要

身体素质是指身体各项机能的健康状况,包括心肺耐力、肌肉力量、柔韧性、耐力和身体成分等,这些有助于个体有效应对日常活动和体育挑战。本文探讨篮球运动员的身体特征,旨在通过独特的身体评估指标提高训练效果,并为提升高校篮球水平和训练标准提供理论框架。该研究采用了数据挖掘中的Apriori关联规则算法。首先,收集并预处理篮球运动员的身体数据。然后,通过关联规则挖掘算法提取频繁项集,生成关联规则,并分析影响运动员身体表现的关键因素。文章结果揭示了不同身体特征之间的潜在关系,并强调了关联规则挖掘在篮球运动员身体评估中的应用前景。

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