Open Access

ARTICLE

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

by Xinbao Wang, Dawu Huang, Xuemin Zhao

Department of Physical Education, Jiang Xi Normal University, China, Nanchang 330022
Address: No.99 Ziyang Avenue, Nanchang City, Jiangxi Province

* Corresponding Author: Xinbao Wang, .

Intelligent Automation & Soft Computing 2020, 26(4), 755-763. https://doi.org/10.32604/iasc.2020.010110

Abstract

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.

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