基于一种贴近度的动态IOWGA算子组合预测模型

Dynamic Induced Ordered Weighted Geometric Averaging Operator Combination Forecasting Model Based on Approach Degree

通过建立基于贴近度的动态IOWGA算子组合预测模型,弥补了基于诱导有序加权几何平均(IOWGA)算子组合预测模型中最优权系数对不同时刻预测精度序列的变化缺乏灵敏度的不足,并且定义了非劣性组合预测、优性组合预测等概念,给出了它们存在的条件.最后通过实例分析,说明了该组合预测方法的有效性和可行性.

A dynamic induced ordered weighted geometric averaging（IOWGA） operator combination forecasting model based on approach degree was proposed.The model overcame the defect that,in（IOWGA） operator combination forecasting model,optimal weights is in lack of sensitivity when forecasting accuracy sequence changes at different time.And the non-inferior combination forecasting and superior combination forecasting were defined.Under certain conditions,the existence of non-inferior and superior combination forecasting was discussed.Finally,an example shows the effectiveness and feasibility of the combination forecasting.