摘要
大学生就业信心指数预测结果的准确性关系到就业政策的制定与实施的效果.提出综合利用各单模型预测信息的组合预测思路,采用层次分析法确定单模型的权重值,构建组合预测模型.结果显示,组合预测模型在拟合期的表现与神经网络模型接近,优于其他两种模型;在预测期远超过其他模型的预测效果.组合预测模型的拟合性能和泛化性能优越,预测信息可作为高校制定相关政策时的重要参考依据.
Employment Confidence Index of college student（ ECI） can be used as a reference to assist the university administrators to formulate work plans and cope with the current employment situation. So,the most accurate forecasting results are needed, which is directly related to the effect of policy formulation and implementation. In order to solve this problem,the advantages and disadvantages of the model of threshold autoregression（ TAR）,back propagation（ BP） and Gray model was analyzed. According to analysis result,we proposal a Combined Forecast model based on the Analytic Hierarchy Process（ CF-AHP）,in which AHP is used to determinate the weight of each single model. The forecast results show that the performance of CF-AHP has a good behavior to other three models,which can be used as an important reference for the university development of relevant policies.
出处
《重庆工商大学学报（自然科学版）》
2015年第9期76-80,92,共6页
Journal of Chongqing Technology and Business University:Natural Science Edition
基金
教育部人文社会科学研究专项任务项目(12JDSZ3041)
安徽高校省级科学研究项目(2011SK637)
安徽工程大学青年科研基金项目(2013YQ38)
关键词
大学生就业
信心指数
组合预测
层次分析法
employment of college students
confidence index
combination forecasting
AHP
