(untitled) (Informatica, 2024)
This study adopts multi-channel data collection strategy, including questionnaire survey, intelligent bracelet data and interview observation, in order to comprehensively understand the characteristics of college students’ physical exercise behavior. Through an analysis of 2000 valid questionnaires and smart bracelet data from 500 students, we found that male college students prefer high-intensity exercise and team sports, while women prefer moderate and moderate exercise such as yoga. As the grade goes up, the proportion of high intensity exercise increases first and then decreases from freshman to senior, while the proportion of low frequency exercise increases gradually, indicating the influence of academic pressure and life rhythm changes on exercise behavior. By using ant colony algorithm to process the data, we get five clusters, each cluster has clearly defined features, so that we can identify and describe different exercise behavior patterns more accurately.