东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2007, Vol. 28 ›› Issue (7): 1061-1064.DOI: -

• 论著 • 上一篇    

多步变权组合预测法及其应用——以预测我国邮政收入及从业人员为例

韩颖;黄小原;李丽君;   

  1. 东北大学工商管理学院;东北大学工商管理学院;东北大学工商管理学院 辽宁沈阳110004;辽宁沈阳110004;辽宁沈阳110004
  • 收稿日期:2013-06-24 修回日期:2013-06-24 出版日期:2007-07-15 发布日期:2013-06-24
  • 通讯作者: Han, Y.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(70572088);;

Method and applications of multi-step variable weight combination forecasting - With China's postal service revenue and staff as example

Han, Ying (1); Huang, Xiao-Yuan (1); Li, Li-Jun (1)   

  1. (1) School of Business Administration, Northeastern University, Shenyang 110004, China
  • Received:2013-06-24 Revised:2013-06-24 Online:2007-07-15 Published:2013-06-24
  • Contact: Han, Y.
  • About author:-
  • Supported by:
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摘要： 针对目前变权重确定没有充分利用已获得的预测信息的实际情况,提出了多步变权组合预测法,并用该预测法对我国2005年到2010年的邮政收入及从业人员进行了预测.多步变权组合预测法通过充分利用已获得的预测信息和多次求解二次规划的方法确定每期权重,并用该权重进行组合预测.结果表明:所提出的组合预测方法合理并具有可操作性;我国未来几年邮政收入将会不断增加,但由于劳动生产率水平的提高和大量富余人员的裁减,邮政从业人员在逐年递减,并且递减趋于缓慢,但我国邮政在促进国民经济发展和吸纳就业人员方面的作用是不容忽视的.

关键词: 变权, 组合预测, 二次规划, 邮政收入, 从业人员

Abstract: In view of the fact that the determination of variable weights has not used fully the acquired forecasting data, a method of multi-step variable weight combination forecasting is proposed to forecast China's postal service revenue and postal staff from 2005 to 2010 as an example in application. The method is used to determine the weights in each period by making full use of acquired forecasting data together with the multi-step solution to quadratic programming, then the weights are reused for combination forecasting. The forecasting results show that the method is rational and easy to operate. China's postal service revenue will increase gradually in the years to come. However, the number of postal staff will decrease because of the improvement of labor productivity and reduction of redundant staff, but the reduction tends to slow down. On the other hand, it should not be overlooked that the postal service can provide jobs for employment and is necessary for national economic growth.

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