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《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:

2019年02期

Page:

23-29

Research Field:

·数学与计算机科学·

Publishing date:

Info

Title:

Research of Mathematics Learning Ability for Graduate StudentsBased on BP Neural Network and Cluster Analysis

Author(s):

Du Shaohong¹; Li Wenshuo¹; 2; Zhen Jiangyi¹; 2; Tan Yuanshun¹

(1.School of Mathematics and Statistics,Chongqing Jiaotong University,Chongqing 400074,China)(2.School of Economics and Management,Chongqing Jiaotong University,Chongqing 400074,China)

Keywords:

BP neural network; correlation analysis; cluster analysis; graduate students; mathematics learning ability

PACS:

G640

DOI:

10.3969/j.issn.1001-4616.2019.02.004

Abstract:

The purpose of this paper is to give some pertinent suggestions for improving postgraduates’ mathematical ability through research and analysis to improve the current situation that graduate students’ mathematics learning ability cannot reach the level of scientific research. This study obtains objective indicators that can comprehensively measure mathematics learning ability through BP neural network to get the math learning ability evaluation score,and uses SPSS software to test the correlation between influencing factors and the indicators,so as to get the factors that significantly affect postgraduates’ mathematics learning ability. Finally,according to the different characteristics of the respondents,the graduate students are clustered,and specific suggestions are given for each type of individuals to improve their mathematics learning ability.

References:

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[2]蔡锦锦. 基于BP神经网络的高校课堂教学质量评价系统的研究与实现[D]. 杭州:浙江工业大学,2009.
[3]冯必波. BP神经网络在教学质量评价体系中的应用[J]. 计算机与数字工程,2010,38(4):97-99.
[4]郑永,陈艳. 基于BP神经网络的高校教师教学质量评价模型[J]. 重庆理工大学学报(自然科学),2015,29(1):85-90.
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[6]王文文,郭宁,王杨. 硕士研究生导学关系现状及影响因素研究[J]. 研究生教育研究,2018(6):76-82.

Memo

Memo:

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Common functions

Last Update: 2019-06-30