Title: Design of data mining system for sports training biochemical indicators based on artificial intelligence and association rules

Authors: Dongbiao Liu

Addresses: School of Computing, Guangxi Police College, Nanning 530028, Guangxi, China

Abstract: Physiological indicators are an important basis for reflecting the physiological health status of the human body and play an important role in medical practice. Association rules have also been one of the important research hotspots in recent years. This study aims to create a data mining system of association rules and artificial intelligence in biochemical indicators of sports training. This article uses Markov logic for network creation and system training, and tests whether the Markov logic network can be associated with the training system. The results show that the accuracy and recall rate obtained are about 90%, which shows that it is feasible to establish biochemical indicators of sports training based on Markov logic network, and the system has universal, guiding and constructive significance, ensuring that the construction of training system indicators will not go in the wrong direction.

Keywords: artificial intelligence; association rules; data mining; biochemical indicators.

DOI: 10.1504/IJDMB.2024.139449

International Journal of Data Mining and Bioinformatics, 2024 Vol.28 No.3/4, pp.236 - 256

Received: 03 Mar 2023
Accepted: 08 Sep 2023
Published online: 02 Jul 2024 *

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