基于BP神经网络模型对我国特殊教育经费投入的统计研究  

Statistical Research on China’s Special Education Funding Input Based on BP Neural Network Modeling

作　　者：程晨 谭志聪 章钟匀 闫世纪 葛志利 CHENG Chen;TAN Zhicong;ZHANG Zhongyun;YAN Shiji;GE Zhili(School of Mathematics and Information Science,Nanjing Normal University of Special Education,Nanjing,210038)

机构地区：[1]南京特殊教育师范学院数学与信息科学学院,南京210038

出　　处：《现代特殊教育》2025年第6期12-17,78,共7页Modern Special Education

摘　　要：“强化特殊教育普惠发展”已成为新时代我国特殊教育发展的方向,而确保充足的经费投入是实现特殊教育普惠发展的前提。通过相关性分析和查阅相关文献,选取了四个对我国特殊教育经费投入产生显著影响的因素,包括我国GDP、人均GDP、教育经费总投入和特殊教育在校学生人数。利用SPSSPRO中的时间序列模型预测了以上四个关键因素在未来十年的发展趋势,然后采用神经网络算法对我国未来的特殊教育经费投入进行了预测。结果显示,我国特殊教育经费在未来十年内将持续增长,但我国特殊教育学校生均经费总体水平不高,因此,亟须改善我国特殊教育经费投入的现状。“Enhancing inclusive development of special education”has emerged as the direction of the development of special education in China in the new era,and ensuring adequate funding is a prerequisite for achieving this inclusive development.Based on Pearson correlation analysis and relevant literature,four factors that significantly influence funding allocation for special education in China have been identified,including China’s GDP,per capita GDP,total education funding,and the number of students enrolled in special education schools.Utilizing the time series model in SPSSPRO,the development trends of these four key factors over the next decade have been predicted.Subsequently,a neural network algorithm is employed to forecast future funding for special education in China.The results indicate that funding for special education in China will continue to increase over the next 10 years.However,the overall level of per capita funding for special schools in China remains low.Therefore,there is an urgent need to improve the current status of funding allocation for special education in China.

关 键 词：神经网络 特殊教育 灰色预测 教育经费 

分 类 号：G760[文化科学—特殊教育学]