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Design of the Sports Training Decision Support System Based on the Improved Association Rule, the Apriori Algorithm

机译:基于改进关联规则的体育训练决策支持系统设计,APRIORI算法

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摘要

In order to improve the judgment decision ability of the sports training effect, a design method of the sports training decision support system based on the improved association rule, the Apriori algorithm is proposed, and a phase space model of the sports training decision support data association rule distribution is constructed. The association rule mining method is used to support the data mining model of sports training, and the decision judgment of the sports training effect is carried out in the mixed cloud computing environment. The fuzzy information fusion and the data structure feature reorganization method is adopted, and the adaptive scheduling and information fusion of the sports training decision support data are realized. The judgment ability of the sports training decision support has improved, and the algorithm design of the sports training decision support system is carried out by using the association rule, the Apriori algorithm. The adaptive resource scheduling and feature recombination are used to improve the Apriori algorithm of the association rules. According to the results of the Apriori feature extraction of the association rules, the decision of the sports training is judged. The simulation results show that this method is used to design the sports training decision support system, which has a good mining performance and strong decision judgment ability for the sports training decision support vector set, and it has a good effect on the sports training decision making.
机译:为了提高体育培训效应的判断决策能力,基于改进关联规则的体育训练决策支持系统的设计方法,提出了APRIORI算法,以及体育训练决策支持数据协会的相空间模型构建规则分布。协会规则挖掘方法用于支持体育培训的数据挖掘模型,并在混合云计算环境中进行体育培训效果的决策判断。采用模糊信息融合和数据结构特征重组方法,实现了体育训练决策支持数据的自适应调度和信息融合。体育训练决策支持的判断能力有所改善,并且通过使用关联规则,APRiori算法进行了运动训练决策支持系统的算法设计。自适应资源调度和特征重组用于改善关联规则的APRIORI算法。根据APRIORI特征提取关联规则的结果,判断运动培训的决定。仿真结果表明,该方法用于设计体育培训决策支持系统,该系统具有良好的采矿性能和体育培训决策支持传染媒介集的强大决策能力,对体育培训决策具有良好影响。

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