摘要
为了提高学生选课的优化配置性能,提高课程资源的利用效能,提出一种基于大数据分析的学生最优选课方案模型的设计方法。首先构建学生优选课方案模型的总体结构模型,采用大数据分析方法进行学生选课资源数据库的信息融合和优化访问设计,结合自适应均衡博弈和灰色关联度分析,得到学生选课的综合决策模型。在Linux内核进行程序开发,基于X86架构建立学生选课系统的交叉编译环境,在虚拟文件系统配置脚本菜单,网络模块集成了HTTP服务器和Telnet服务器功能,实现课程信息的数据共享和远程传输。最后进行系统软件开发和调试分析,结果表明,该选课方案模型具有较好的大数据分析能力,实现课程最优化配置和选取,模型的可靠性较强。
In order to improve the optimal allocation performance in students′course selection and utilization efficiency ofcurriculum resources,a design method of a course selection model based on large data analysis is proposed.The overall structure model of student optimal course selection model is constructed firstly.A large data analysis method is used to conduct information fusion and optimal access design of student course resource database to get comprehensive decision model of studentcourse selection by combining adaptive equilibrium with grey correlation analysis.The program development is performed inLinux kernel.The cross compile environment for student elective system is established based on X86architecture.A script menuis collocated in the virtual file system.HTTP server and telnet server functions are integrated in the network module to realize data sharing and remote transmission of the curriculum information.The system software development and debugging analysis results show that the course selection scheme model has good data analysis ability and strong reliability,and can realize the optimization configuration and selection of courses.
作者
史金梅
夏伟
SHI Jinmei;XIA Wei(Lüliang University,Lüliang 033000,China;Zhejiang Sci-Tech University,Hangzhou 310018,China)
出处
《现代电子技术》
北大核心
2017年第14期30-32,共3页
Modern Electronics Technique
基金
国家自然科学基金(50875245)
关键词
大数据分析
选课
模型设计
信息融合
big data analysis
course selection
model design
information fusion
作者简介
史金梅（1981—），女，山西太谷人，讲师，教育技术学硕士。研究方向为教育信息化;夏伟（1988—），男，山东菏泽人，硕士。主要研究领域为模式识别和图像处理
