基于模糊聚类分析法的学生成绩分类

创新创业理论研究与实践 ›› 2022, Vol. 5 ›› Issue (8): 168-170.

基于模糊聚类分析法的学生成绩分类

于海洋¹, 李秀文²

1.大连民族大学机电工程学院,辽宁大连 116600;
2.大连民族大学理学院,辽宁大连 116600

出版日期:2022-04-25 发布日期:2022-10-28
通讯作者: 李秀文（1984-）,女,辽宁辽阳人,博士,讲师,研究方向：计算数学、统计学,邮箱：lixuwen@dlnu.edu.cn。
作者简介:于海洋（1983-）,男,辽宁辽中人,博士,讲师,研究方向：智能机器人技术。
基金资助:
2021年大连民族大学一流本科课程建设“回归分析”（编号：YLKC21081）; 2021年大连民族大学本科教育教学改革研究与实践项目“以学为中心的回归分析课程教学改革研究”（编号：YB2021044）

Classification of Students' Grades based on Fuzzy Cluster Analysis

YU Haiyang¹, LI Xiuwen²

1. School of Mechanical and Electrical Engineering, Dalian Minzu University, Dalian Liaoning, 116600, China;
2. College of Science, Dalian Minzu University, Dalian Liaoning, 116600, China

Online:2022-04-25 Published:2022-10-28

摘要/Abstract

摘要： 为具体掌握学生专业课的学习情况,根据学生专业课试卷各题型的得分,利用模糊聚类分析法对学生成绩进行分类。选取自动化专业学生的专业课期末考试成绩作为统计指标,对数据标准化处理,利用最大最小法建立模糊相似矩阵,通过传递闭包法作模糊聚类分析。结果表明,模糊聚类分析法可以更科学地对学生成绩进行分类,有助于掌握学生学习情况,有效提高学生的学习成绩。

关键词: 试卷分析, 学生成绩, 模糊聚类分析, 模糊相似矩阵

Abstract: In this paper, in order to grasp the learning situation of students' professional courses, according to the scores of each item type of students' professional course test paper, the fuzzy cluster analysis method is used to classify students' grades. This paper selects students' scores as statistical indicators, standardizes the data, uses the maximum minimum method to establish the fuzzy similarity matrix, and uses the transitive closure method for fuzzy cluster analysis. The results show that the fuzzy cluster analysis method can classify the students' grades more scientifically, which is helpful to master the students' learning situation and improve their grades effectively.

Key words: Examination paper analysis, Student achievement, Fuzzy cluster analysis, Fuzzy similarity matrix

中图分类号:

O159

于海洋, 李秀文. 基于模糊聚类分析法的学生成绩分类[J]. 创新创业理论研究与实践, 2022, 5(8): 168-170.

YU Haiyang, LI Xiuwen. Classification of Students' Grades based on Fuzzy Cluster Analysis[J]. The Theory and Practice of Innovation and Enntrepreneurship, 2022, 5(8): 168-170.