大数据背景下高校投资方案研究  

Investment Research of Universities under the Background of Big Data

作　　者：蒋辉[1] 曾昱为 姚秀燕 JIANG Hui;ZENG Yuwei;YAO Xiuyan(School of Information Science and Technology, Huizhou University, Huizhou 516007, Guangdong, China;School of Economics and Management, Beijing Jiaotong University, Haiding 100044, Bejing, China;School of Mathematics and Big Data, Huizhou University, Huizhou 516007, Guangdong, China)

机构地区：[1]惠州学院信息科学技术学院,广东惠州516007 [2]北京交通大学经济管理学院,北京100044 [3]惠州学院数学与大数据学院,广东惠州516007

出　　处：《惠州学院学报》2017年第3期1-6,共6页Journal of Huizhou University

基　　金：国家社科基金一般项目(15BTJ024);教育部人文社会科学规划基金项目(14YJAZH040);广东省大学生科技创新培育专项基金项目(pdjh2016a0475)

摘　　要：根据2016年MCM题C数据,从地理优势、民族、学费考虑美国高校公平,选取了体现高校公平的8项指标,分别采用基尼系数和层次分析确定其客观、主观权重,得到各高校的公平系数;同时,运用相关分析和逐步回归挑选高回报专业,选取体现高校效益的35个指标,采用因子分析得到各高校的效益系数;以公平系数与效益系数的综合分值可确定待投资高校的投资份额.According to the data of2016MCM problem C,we consider American university fairness from the geographical advantage,ethnicity and tuition.Eight indexes of university fairness are selected to determine each university objective and subjective weight by the Gini coefficient and analytic hierarchy,respectively.Then,fair coefficient of each university is obtained.Meanwhile,we adopt correlation analysis and stepwise regression to select the high return majors.Thirty-five indexes reflected the university efficiency are chosen to get the efficiency coefficient by factor analysis.The comprehensive score of the fairness and efficiency coefficient could be used to identify the share of investment to universities.

关 键 词：公平系数 效益系数 投资分析 

分 类 号：O175.14[理学—数学]