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基于L1范数IOWGA算子的大学生就业信心指数组合预测模型
引用本文:石琼强,杨桂元.基于L1范数IOWGA算子的大学生就业信心指数组合预测模型[J].襄樊学院学报,2014(2):8-11.
作者姓名:石琼强  杨桂元
作者单位:安徽财经大学统计与应用数学学院,安徽蚌埠233030
基金项目:国家社科基金项目(12BTJ008); 安徽财经大学研究生创新基金项目(ACYC2013052)
摘    要:大学生就业信心指数的预测可以在一定程度上了解大学生就业信心的变化趋势.因此,文章建立了基于L1范数的诱导有序加权几何平均(IOWGA)算子的组合预测模型及预测有效度评价指标体系,以山东省德州市某高校2000—2012年大学生就业信心指数数据,对大学生就业信心指数中的全局信心指数进行分析预测,并与采用GM(1,N)预测模型、单指数平滑预测模型和ARMAX预测模型分析结果从预测精度、预测模型有效性上进行比较.结果表明:基于L1范数的IOWGA算子组合预测模型比其他三种单项预测方法预测方法精度更高且为优性组合预测,本模型对大学生就业信心指数预测是可行的,可以用于对大学生就业信心的定量研究.

关 键 词:大学生就业信心指数  IOWGA算子  L1范数  GM(1  N)模型  优性组合预测

Combination Forecasting Model for Graduate Employment Confidence Index Based on the IOWGA Operator of the L1 norm
SHI Qiongqiang,YANG Guiyuan.Combination Forecasting Model for Graduate Employment Confidence Index Based on the IOWGA Operator of the L1 norm[J].Journal of Xiangfan University,2014(2):8-11.
Authors:SHI Qiongqiang  YANG Guiyuan
Institution:(School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu 233030, China)
Abstract:Forecasting of graduate employment confidence index is helpful to know more about the changing trend of graduate employment confidence in a certain sense. It establishes a combination forecasting model based on the induced ordered weighted geometric averaging(IOWGA) operator of the L1 norm, and it offers a evaluation index system for validity. Based on the employment confidence index of graduate from some college in Dezhou, Shandong Province during 2000 to 2012, it analyzes the overall situation confidence index, with the GM(1, N) model, the single exponential smoothing model and ARMAX model employed at the same time. The conclusion is that the combination forecasting model performs better about the accuracy than the other three methods. It proves that the combination forecasting model is feasilbe to forecast the graduate employment confidence index and can be used for the quantiative research of the graduate employment confidence.
Keywords:Graduate employment confidence index  IOWGA operator  L1 norm  GM(1  N) model  Superior combination forecasting
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