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计算机系统应用英文版:2018,27(3):168-172

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基于改进AHP-BP神经网络的幼儿发展评价模型

李顺喜^1,2, 蒲宝明², 韩爽^1,2, 李相泽³, 张笑东^1,2, 王帅^1,2

(1.中国科学院大学, 北京 100049;2.中国科学院沈阳计算技术研究所, 沈阳 110168;3.东北大学计算机科学与工程学院, 沈阳 110819)

Preschool Child Health Assessment Model Based on Improved AHP-BPNN

LI Shun-Xi^1,2, PU Bao-Ming², HAN Shuang^1,2, LI Xiang-Ze³, ZHANG Xiao-Dong^1,2, WANG Shuai^1,2

(1.University of Chinese Academy of Sciences, Beijing 100049, China;2.Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China;3.School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China)

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本文已被：浏览 2276次下载 2934次
Received:June 27, 2017 Revised:July 10, 2017

中文摘要: 现有的幼儿健康发展评估方案有着评估周期长、个人主观意识强以及评价指标单一等缺陷，对幼儿的长期发展以及学前教育的信息化有着诸多方面的限制和影响.因此，本文引入了改进的AHP-BPNN评估方法，根据幼儿发展的生理和心理特性，利用AHP层次分析方法建立科学的、多维化的评价体系，同时对各项评价指标初始化；利用改进的BPNN对评价指标权重进行分析和优化，得到最优的参数解.通过对沈阳某幼儿园214名幼儿90天的连续实践观察表明，本文所提的方法大大减少了教师的主观性评价，使评价体系更加科学、合理和完善，对幼儿健康发展给出了全面性的指导.

中文关键词: 幼儿健康评估模型层次分析方法 BP神经网络

Abstract:The existing healthy development evaluation scheme has defects like a long life cycle, subjective sense, single evaluation index and many others, which has restrictions on the children's long-term development and preschool education informatization. Therefore, this paper introduces the evaluation method of AHP-BPNN. According to the physiological and psychological characteristics of children's development, it uses the AHP analytic hierarchy process to establish scientific and multidimensional evaluation system. Meanwhile, the initial weights is initialized. Then it makes the improved BPNN analysis to optimize the weight, to get a more optimal parameter solution. Based on the continuous practice of 214 children in a kindergarten in Shenyang for 90 days of observation, it shows that the proposed method greatly reduces the subjectivity of teacher evaluation, makes the evaluation system more scientific, reasonable and perfect, and gives a comprehensive guide.

keywords: preschool child health assessment model AHP BP neural network

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Author Name	Affiliation	E-mail
LI Shun-Xi	University of Chinese Academy of Sciences, Beijing 100049, China Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China	easyboy519@163.com
PU Bao-Ming	Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China
HAN Shuang	University of Chinese Academy of Sciences, Beijing 100049, China Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China
LI Xiang-Ze	School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China
ZHANG Xiao-Dong	University of Chinese Academy of Sciences, Beijing 100049, China Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China
WANG Shuai	University of Chinese Academy of Sciences, Beijing 100049, China Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China

Author Name	Affiliation	E-mail
LI Shun-Xi	University of Chinese Academy of Sciences, Beijing 100049, China Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China	easyboy519@163.com
PU Bao-Ming	Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China
HAN Shuang	University of Chinese Academy of Sciences, Beijing 100049, China Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China
LI Xiang-Ze	School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China
ZHANG Xiao-Dong	University of Chinese Academy of Sciences, Beijing 100049, China Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China
WANG Shuai	University of Chinese Academy of Sciences, Beijing 100049, China Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China

引用文本：
李顺喜,蒲宝明,韩爽,李相泽,张笑东,王帅.基于改进AHP-BP神经网络的幼儿发展评价模型.计算机系统应用,2018,27(3):168-172
LI Shun-Xi,PU Bao-Ming,HAN Shuang,LI Xiang-Ze,ZHANG Xiao-Dong,WANG Shuai.Preschool Child Health Assessment Model Based on Improved AHP-BPNN.COMPUTER SYSTEMS APPLICATIONS,2018,27(3):168-172