Construction and Effect Analysis of College Students' Physical Education Teaching Mode Based on Data Mining Algorithm

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Abstract

With the wide application of computer technology, communication technology, network technology, and multimedia technology in modern education, teaching methods tend to be diversified and scientific. Based on the DM (data mining) algorithm, this paper implements a sports achievement management system. Through this system, the efficiency of inputting and counting students' achievements can be improved, and teachers can be freed from the complicated achievement management. Aiming at the problem that SVM (Support Vector Machine) is slow in training large sample sets in DM classification, a DM classification algorithm based on improved SVM, PSO_SVM, is proposed, which applies the density of adjacent samples to the design of membership function to reduce the influence of noise points on classification. The results show that the training time of this algorithm is increased by 54.26 s and 55.69 s compared with SVM and K-means, respectively, and the accuracy is increased by 35.62%. The results obtained by the DM algorithm will be helpful for teachers to diagnose teaching problems and construct PET (physical education teaching) model for college students with characteristics.

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APA

Wang, P. (2022). Construction and Effect Analysis of College Students’ Physical Education Teaching Mode Based on Data Mining Algorithm. Journal of Sensors. Hindawi Limited. https://doi.org/10.1155/2022/1028962

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