Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

October 9, 2024


Pages


DOI

Article

Prediction of Historical Development Trends of Traditional Wushu Culture Based on Data Mining

Check for updates


Authors

Mingjie Zheng Affiliation:
College of Physical Education and Humanities and Arts, China University of Petroleum (Beijing), Beijing, 102200, China.
and Ruyu Kong Affiliation:
Tianzhu First Primary School, Shunyi District, Beijing, 101312, China.


Abstract

This paper first introduces the use of data mining technology in the development of the traditional culture of martial arts. This paper begins with the optimized FCM algorithm, obtains the fuzzy pattern through the affiliation function, and builds a prediction model using the clustering algorithm of fuzzy time series. The historical development trend of Chinese martial arts traditional culture is predicted using this model. The results show that the process of defuzzification prediction divides the literature on the development of traditional culture of martial arts into five groups, and the five clustering centers are A1: 3055-4693, A2: 5603-6919, A3: 6388-7497, A4: 7984-8150, and A5: 8876-9483. The predicted values of the FCM algorithm model for the literature of the first group to the fifth group are respectively 3735.3, 5374.05, 6351.57, 7048.56, and 9144.31. The average error of prediction is 0.134, 0.062, 0.094, 0.126, and 0.025, respectively. The average prediction accuracies of the predictions are all >85%, and in particular, the accuracy of predicted values for the fifth group reaches 98%. It can be seen that the prediction model proposed in this paper is effective in predicting the historical development trend of the traditional culture of martial arts.


Keywords

FCM algorithm, Fuzzy time series prediction model, Affiliation function, Martial arts traditional culture, 01A12


Citation

Zheng, M. & Kong, R. (2024). Prediction of historical development trends of traditional wushu culture based on data mining. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-2898

Published by: Engineering Journals

Engineering Journals Logo