|本期目录/Table of Contents|

[1]孙浩,杨桂元*.基于一种贴近度的IOWHA算子预测模型的性质研究[J].延边大学学报(自然科学版),2017,(02):113-118.
 SUN Hao,YANG Guiyuan*.Study on properties of induced ordered weighted harmonic averaging operator based on combination forecasting[J].Journal of Yanbian University,2017,(02):113-118.
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基于一种贴近度的IOWHA算子预测模型的性质研究()
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《延边大学学报(自然科学版)》[ISSN:1004-4353/CN:22-1191/N]

卷:
期数:
2017年02期
页码:
113-118
栏目:
基础科学研究
出版日期:
2017-07-20

文章信息/Info

Title:
Study on properties of induced ordered weighted harmonic averaging operator based on combination forecasting
作者:
孙浩 杨桂元*
安徽财经大学 统计与应用数学学院, 安徽 蚌埠 233030
Author(s):
SUN Hao YANG Guiyuan*
School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu 233030, China
关键词:
组合预测 贴近度 IOWHA算子
Keywords:
combination forecasting closeness degree IOWHA operator
分类号:
F224.0
DOI:
-
文献标志码:
A
摘要:
为了克服传统的单项预测方法选取固定参数所带来的不足,在诱导有序加权调和平均算子(IOWHA算子)的基础上,引入贴近度构建了基于一种贴近度的IOWHA算子的最优组合预测模型,对该模型的预测精度、优性及非劣性给出定义,并从理论的角度探究了其非劣性组合预测、优性组合预测的存在性的充分条件.实例分析表明,该组合预测模型优于传统的组合预测模型,能够充分利用各个单项预测方法的信息并能提高预测精度,是一种优性组合预测.
Abstract:
In order to overcome the defects in using the single forecasting method to choose the fixed coefficient, the paper introduced closeness degree based on induced ordered weighted harmonic averaging operator(IOWHA operator), constructed an optimal combination forecasting model of IOWHA based on closeness degree, then define the conception of prediction accuracy, the superior combination forecasting and no inferior combination forecasting. The sufficient conditions for the existence of non-inferiority combination forecasting and superior combination forecasting are studied from the perspective of theory. The example illustrated that the combination forecasting model can make full use of the information from the single forecasting method, the forecasting precision is superior to the traditional single forecasting model as well. It is concluded that the method is a superior combination forecasting method.

参考文献/References:

[1] Bates J M, Granger C W J. Combination of forecasts[J]. Operation Research Quarterly, 1969,20(4):451-468.
[2] Yager R R. On ordered weighted averaging aggregation operators in multicriteria decision making[J]. IEEE Transactions on Systems, Man, and Cybernetics, 1988,18(1):183-190.
[3] Filev D, Yager R R. On the issue of obtaining OWA operator weights[J].Fuzzy Sets and Systems, 1998,94(2):157-169.
[4] 马永开,杨桂元,唐小我.非负权重组合预测的冗余定理[J].系统工程理论方法应用,1995,4(4):33-39.
[5] 唐小我,马永开,曾勇,等.现代组合预测和组合投资决策方法及应用研究[M].北京:科学出版社,2003.
[6] 姜晨,徐宗昌,肖国军.用神经网络组合预测法估算反舰导弹研制费用[J].系统工程与电子技术,2004,26(3):348-349,372.
[7] 陈华友.组合预测方法有效性理论及其应用[M].北京:科学出版社,2008.
[8] 滕云龙,师奕兵,康容雷.软件可靠性组合预测模型研究[J].计算机应用,2008,28(12):3092-3094.
[9] 谢宇婧.货币供应量M2预测精度:基于组合模型的改进[J].统计与决策,2017(5):93-97.
[10] 李得伟,颜艺星,曾险峰.城市轨道交通进站客流量短时组合预测模型[J].都市快轨交通,2017(1):54-58.
[11] 陈华友,刘春林.基于IOWA算子组合预测方法[J].预测,2003,22(6):61-65.
[12] 陈华友,刘春林,盛昭瀚.IOWHA算子及其在组合预测中的应用[J].中国管理科学,2004(5):36-41.
[13] 李洪岩,陈华友.基于Theil不等系数的IOWHA算子组合预测模型及其应用[J].数学的实践与认识,2011(11):105-112.
[14] 孙浩,杨桂元.基于一种贴近度的IGOWLA算子的最优组合预测模型[J].延边大学学报(自然科学版),2017,43(1):19-24.
[15] 刘法贵,赵娟.模糊贴近度及应用[J].华北水利水电学院学报,2006,27(3):104-106.
[16] 储震,杨桂元.基于灰关联度的IGOWLA算子中国楼市库存的预测分析[J].佳木斯大学学报(自然科学版),2016,34(4):599-605.

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备注/Memo

备注/Memo:
收稿日期: 2017-04-09 基金项目: 国家社会科学基金资助项目(12BTJ008)
*通信作者: 杨桂元(1957—),男,教授,研究方向为预测理论与方法、金融计量分析.
更新日期/Last Update: 2017-06-20