摘要
针对目前高职院校思政教育工作存在的信息反馈滞后、预警干预机制不完善、风险管控能力较弱等问题,开发了一款基于改进SVM算法的思政教育动态预警系统。通过构建体量较大的基于用户行为的日志数据库,引入改进过的支持向量机(SVM)算法并融入预警分类器建立面向思政教育动态预警模型,在Matlab2016b环境下进行模型效能仿真验证,较好解决了多维应用背景下的高校思政教育动态预警过程中人力耗费与实际效能失衡、信息反馈滞后等问题,具有动态预警精准、泛化预警能力强、风险管控变化趋势预估效率高等优势。以我国东部某高职院校为效能评价载体,利用VS2012平台开发了验证环境并对模型进行了实证分析,分析结果表明所提模型可以实现全方位的高校思政教育动态预警,在预警适应性、模型拟合度、信息过载处理效率等方面具有明显优势。
Aiming at the problems of lag in information feedback,imperfect early warning intervention mechanism and weak risk management and control ability in the ideological and political education work of higher vocational colleges,a dynamic early warning system based on improved SVM algorithm was developed.By constructing a large user database based on user behavior,an improved support vector machine(SVM)algorithm is introduced and an early warning classifier is built to establish a dynamic early warning model for ideological and political education.The model performance simulation is validated in Matlab 2016b environment.It solves the problems of imbalance between manpower consumption and actual efficiency and lag of information feedback in the dynamic early warning process of ideological and political education in colleges and universities under the background of multi-dimensional application.It has the advantages of dynamic early warning accuracy,strong generalized early warning ability,and high risk estimation performance.Taking a higher vocational college in eastern China as the effectiveness evaluation carrier,the verification environment is developed by using VS2012 platform,and the model is empirically analyzed.The analysis results show that the model proposed in this paper can realize the dynamic early warning of ideological and political education in colleges and universities.Model fit,information overload processing efficiency and other aspects have obvious advantages.
作者
席卫华
XI Weihua(Wuxi Electrical and Mechanical Branch Courts, Jiangsu Union Technical Institute, Wuxi 214028, China)
出处
《微型电脑应用》
2020年第9期27-31,共5页
Microcomputer Applications
基金
江苏省教委现代教育技术研究项目(2019-R-69341)
无锡市哲学社会科学课题(WXSK19-B-25)。
关键词
思政教育
动态预警模型
改进支持向量机算法
预警分类器
系统开发
ideological and political education
dynamic early warning model
improved support vector machine algorithm
early warning classifier
system development
