[1]杜绍洪,李文烁,郑江溢,等.基于BP神经网络与聚类分析的数学创新能力研究[J].南京师范大学学报(自然科学版),2019,42(02):23-29.[doi:10.3969/j.issn.1001-4616.2019.02.004]
　Du Shaohong,Li Wenshuo,Zhen Jiangyi,et al.Research of Mathematics Learning Ability for Graduate StudentsBased on BP Neural Network and Cluster Analysis[J].Journal of Nanjing Normal University(Natural Science Edition),2019,42(02):23-29.[doi:10.3969/j.issn.1001-4616.2019.02.004]
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基于BP神经网络与聚类分析的数学创新能力研究()
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《南京师范大学学报》（自然科学版）[ISSN:1001-4616/CN:32-1239/N]

卷:
第42卷
期数:
2019年02期
页码:
23-29
栏目:
·数学与计算机科学·
出版日期:
2019-06-30

文章信息/Info

Title:
Research of Mathematics Learning Ability for Graduate StudentsBased on BP Neural Network and Cluster Analysis
文章编号:
1001-4616(2019)02-0023-07
作者:
杜绍洪1; 李文烁1; 2; 郑江溢1; 2; 谭远顺1
(1.重庆交通大学数学与统计学院,重庆 400074)(2.重庆交通大学经济与管理学院,重庆 400074)
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)
关键词:
BP神经网络; 相关性分析; 聚类分析; 研究生; 数学学习能力
Keywords:
BP neural network; correlation analysis; cluster analysis; graduate students; mathematics learning ability
分类号:
G640
DOI:
10.3969/j.issn.1001-4616.2019.02.004
文献标志码:
A
摘要:
通过研究和分析给出提高研究生数学学习能力的针对性建议,以改善目前研究生数学学习能力跟不上科研水平的现状. 该研究通过BP神经网络得出能够全面衡量数学学习能力的客观指标,得出数学学习能力的评价得分,并利用SPSS软件进行影响因素与该指标的相关性检验,以得出显著影响研究生数学学习能力的因素. 最后,根据调查对象的不同特征将研究生个体进行聚类,对每一类个体提升数学学习能力给出针对性建议.
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.

参考文献/References:

[1] 周长城,任传波,高松,等. 创新数学思维与研究生创新能力培养研究[J]. 高等工程教育研究,2008,S2.
[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.
[5]冯岩松. SPSS 22.0统计分析应用教程[M]. 北京:清华大学出版社,2015.
[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.

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备注/Memo

备注/Memo:
收稿日期:2018-03-17.
基金项目:国家自然科学基金(11801047)、重庆市高校创新团队项目(CXTDX201601022)、重庆市自然科学基金(CSTC2018jcyjAX0490).
通讯联系人:谭远顺,博士,教授,研究方向:应用数学. E-mail:tanys625@163.com
更新日期/Last Update: 2019-06-30