基于对数灰关联度的IGOWLA算子最优组合预测模型  

The Combination Forecasting Model Based on Degree of Logarithm Grey Incidence and Induced Geometric Ordered Weighted Logarithm Averaging( IGOWLA) Operator

作　　者：吴齐[1] 杨桂元[1] 储震[1] 

机构地区：[1]安徽财经大学数量经济研究所,安徽蚌埠233030

出　　处：《淮阴师范学院学报（自然科学版）》2016年第2期114-119,共6页Journal of Huaiyin Teachers College;Natural Science Edition

基　　金：国家社科基金资助项目"组合预测模型与方法创新及其优化理论研究"(12BTJ008);安徽财经大学研究生科研创新基金资助项目(ACYC2015081)

摘　　要：在对数灰关联度和诱导广义有序加权对数平均算子(IGOWLA)等概念的基础上,构建了基于对数灰关联度的IGOWLA算子的最优组合预测模型,并引入组合预测模型的优性及非劣性定义.实例计算结果表明,提出的方法确为一种优性组合预测,能够有效地提高预测精度.In this paper,a new combination forecasting model was proposed based on degree of logarithm grey incidence and induced geometric ordered weighted logarithm averaging（ IGOWLA） operator by combining the induced ordered geometric ordered weighted logarithm averaging operator and the degree of grey incidence.At the same time,the conception of superior combination forecasting and noninferior combination forecasting was given. Finally,an example is illustrated by using the model. The example showed that the combination forecasting model was effective and reasonable,and it was superior combination forecasting.

关 键 词：对数灰色关联度 IGOWLA算子 优性组合预测 

分 类 号：O224[理学—运筹学与控制论]