Designing Badminton Training System Using Improved Apriori Association Rule Algorithm
C. T. Cheng, Chengye Dai · 2024
The demand for designing and implementing an effective sports training system is growing rapidly using data mining technology. However, providing efficient training measures with proper use of scientific data has become a major drawback. For effective design of the training systems for the badminton player, the proposed research focused on designing and implementing the training system using Improved Apriori Association Rule Mining (IAARM) algorithm. Initially, the data flow is analysed from the server databases to make use of information like training schedules, score cards for the coach to use, followed by applying the association rule mining to generate a very large number of association rules based on the parameter setting. The association rules are then discovered using the improved apriori for achieving the decision-making in sports training patterns. This system enables the coaches to choose the trained athletes and score cards to measure the quality of training. The experimental results showed that the proposed IAARM achieved minimum support of 3.53 and minimum confidence of 40.63 at 10 ms when compared to the result of existing methods such as Discrete Dynamic Modeling based Apriori (DDM-Apriori) and Apriori algorithm.