Evaluation Method of Wushu Teaching Quality Based on Fuzzy Clustering
Author(s) -
Zhechun Hu,
Yunxing Wang
Publication year - 2022
Publication title -
security and communication networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.446
H-Index - 43
eISSN - 1939-0114
pISSN - 1939-0122
DOI - 10.1155/2022/3823979
Subject(s) - computer science , cluster analysis , quality (philosophy) , fuzzy logic , martial arts , reliability (semiconductor) , point (geometry) , data mining , grid , fuzzy clustering , stability (learning theory) , artificial intelligence , machine learning , mathematics , philosophy , power (physics) , physics , geometry , archaeology , epistemology , quantum mechanics , history
The existing teaching quality evaluation methods cannot calculate the distance between the data points of teaching dataset and the center points of the large density grid, which leads to the poor classification of teaching data and the low accuracy of teaching quality evaluation. Therefore, a method of teaching quality evaluation of Wushu based on fuzzy clustering is proposed. In order to improve the comprehensiveness of teaching quality evaluation, the lost data of teaching resources were recovered. Based on this, the grid index of martial arts teaching data is established, and the relationship model between teaching quality and martial arts achievement is constructed. Based on the characteristics of Wushu teaching resources, the fuzzy clustering method is introduced to calculate the distance between each data point and the grid center with high data density. The experimental results show that the evaluation accuracy of the teaching quality is high, and the lost data can be accurately recovered. The evaluation efficiency, reliability, and stability of Wushu teaching quality are ideal.
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