GA-PCA模型在高校教育管理中的应用效果研究
Analysis of the Application Effect of GA-PCA Model in Higher Education Management
郑妮1
作者信息
- 1. 安徽新华学院(安徽 合肥 230088)
- 折叠
摘要
教育管理系统中存储着大量的学生成绩数据,为了更好地挖掘这些数据潜在信息,推动教育管理的进一步发展,该文利用模糊神经网络对学生成绩进行预测分析,通过主成分分析方法对多维数据进行降维,采用遗传算法对模糊神经网络的前件参数进行优化,通过仿真实验对模型进行性能验证.结果表明,改进的模型相较于原模型具有显著的性能提升,拟合性与预测精度均发生明显变化,故构建的学生学习预测模型具有较好的性能,能够应用于高校教育管理.
Abstract
A large amount data of student performance is stored in the educational management system.In order to better explore the potential information in these data and promote the further development of educational management,this article intends to use fuzzy neural networks to predict and analyze student performance,reduce the dimensionality of multidimensional data through principal component analysis,optimize the antecedent parameters of the fuzzy neural network using genetic algorithm,and verify the performance of the model through simulation experiments to improve the overall performance of the model.After the comparative experiment,the improved model show significant performance improvement com-pared with the original model,with significant changes in fitting and prediction accuracy.Therefore,the constructed student learning prediction model has good performance and practical application ability in higher education management.
关键词
教育管理/遗传算法/主成分分析/模糊神经网络Key words
educational management/genetics algorithm/principal component analysis/fuzzy neural net-work引用本文复制引用
基金项目
安徽省省级质量工程项目线上线下混合式课程建设项目(2020xsxxkc219)
安徽省省级质量工程教育教学改革研究重点项目(2020jyxm0803)
安徽省高等学校思想政治工作中青年骨干队伍建设项目(sztsjh2019-8-39)
出版年
2024
NETL
NSTL
万方数据