计算机应用与软件2025，Vol.42Issue(7)：22-26,50,6.DOI:10.3969/j.issn.1000-386x.2025.07.003
基于机器学习方法的网瘾及学业预警系统设计
INTERNET ADDICTION AND STUDY EARLY WARNING SYSTEM BASED ON MACHINE LEARNING METHODS
摘要
Abstract
In view of Internet addiction and academic warning for university students,questionnaires including student performance,design demography,individual behavior,social relationships and Internet addiction were used as study data,and we proposed two machine learning methods of students'internet addiction and academic warning research based on BP neural network and random forest.The study provided early warning mechanism for teachers and students,and analyzed the important influencing factors to achieve precise intervention.Through simulation analysis,BP neural network and random forest algorithms were chosen to train internet addiction and academic study model respectively,and the accuracy reached 92.286%and 92.742%respectively.The study provided early warning mechanism for teachers and students,and it has certain academic and application values.关键词
网瘾预测/学业预测/BP神经网络/随机森林Key words
Internet addiction prediction/Academic warning/BP neural network/Random forest分类
信息技术与安全科学引用本文复制引用
王颖,王佳棋,夏瑜,严卫,朱海霞,厉业强,汝吉东,刘洋..基于机器学习方法的网瘾及学业预警系统设计[J].计算机应用与软件,2025,42(7):22-26,50,6.基金项目
教育部人文社会科学研究规划基金项目(21YJAZH091) （21YJAZH091）
江苏省教育科学"十四五"规划课题(T-c/2021/93) （T-c/2021/93）
江苏高校哲学社会科学研究项目(2021SJA1426) （2021SJA1426）
"纺织之光"中国纺织工业联合会高等教育教学改革研究项目(2021BKJGLX206) （2021BKJGLX206）
中国高等教育学会"十四五"规划专项课题(21JSYB16) （21JSYB16）
全国高等院校计算机基础教育研究会项目(2021-AFCEC-140,CERACU2021R11). （2021-AFCEC-140,CERACU2021R11）
