Rules Mining of Sports Training Data Management Based on Fuzzy Clustering Algorithm

Yinyue Tan
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Abstract

The application of scientific training theory and sports training means to the management of college students' sports training can effectively improve the physical quality of college students. In order to solve the shortcomings of the existing research on sports training data management, this paper discusses the association rule mining algorithm, data mining objects and sports application decision support system, as well as fuzzy clustering algorithm, and investigates and discusses the establishment of knowledge base and data mining tools. A mining model of sports training data management rules based on fuzzy clustering algorithm is established. The experimental data show that the running time of the algorithm decreases with the support, and the running time is only 30s when the support is 0.3. Therefore, it is verified that the algorithm has a good effect in the mining of sports training data management rules.
基于模糊聚类算法的运动训练数据管理规则挖掘
将科学的训练理论和运动训练手段应用到大学生运动训练管理中,可以有效地提高大学生的身体素质。为了解决现有运动训练数据管理研究的不足,本文讨论了关联规则挖掘算法、数据挖掘对象和运动应用决策支持系统以及模糊聚类算法,并对知识库的建立和数据挖掘工具进行了研究和探讨。建立了基于模糊聚类算法的运动训练数据管理规则挖掘模型。实验数据表明,该算法的运行时间随着支持度的增加而减少,当支持度为0.3时,运行时间仅为30s。由此验证了该算法在运动训练数据管理规则挖掘中具有良好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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