数据驱动的高校学生心理健康风险预测研究  

Research on the data-driven mental health risk prediction of college students

作　　者：程俊俊 冯占春[1] CHENG Jun-jun;FENG Zhan-chun(School of Medicine and Health Management,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430030,China;Jingchu University of Technology,Jingmen 448000,Hubei Province,China)

机构地区：[1]华中科技大学同济医学院医药卫生管理学院,武汉430030 [2]荆楚理工学院,湖北荆门448000

出　　处：《信息技术》2022年第6期1-5,11,共6页Information Technology

基　　金：国家自然科学基金面上项目(72074088)。

摘　　要：为了准确描述高校学生心理健康风险变化特点,提出了基于数据驱动的高校学生心理健康风险预测。首先采集高校学生心理健康风险数据,利用K-means聚类方法对心理健康风险数据进行预处理,然后采用模糊综合评判方法依据聚类结果构建评判矩阵,得到相应权重,最后依据最大隶属度原则得到高校学生心理健康风险预测结果。实验结果表明,文中方法可有效预测高校学生心理健康风险数据,预测结果的可信度较高。In order to accurately describe the characteristics of college students’mental health risk changes,a data-driven college students’mental health risk prediction method is proposed.Firstly,the high mental health risk data is collected,and the K-means clustering method is used to preprocess the mental health risk data.Then,the fuzzy comprehensive evaluation method is used to construct the evaluation matrix according to the clustering results,and the corresponding weights are obtained.Finally,the prediction results of college students’mental health risk are obtained according to the maximum membership principle.The experiment results show that this method can effectively predict the mental health risk of college students,and the reliability of the prediction results is high.

关 键 词：数据驱动 高校学生 心理健康 风险预测 准则函数 

分 类 号：TP315[自动化与计算机技术—计算机软件与理论]