基于改进的灰色关联度 IOWHA 运算符的区间类型组合预测模型

Feng Xu, Xiaowei Cai
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引用次数: 0

摘要

为了提高区间数预测的精度,本文提出了一种基于改进的灰色关联度和 IOWHA 算子的新型区间数组合预测模型。将区间数转化为等效信息的中心和半径,引入 IOWHA 算子,以区间数预测精度为诱导因素,以提高灰色关联度为最优准则,构建基于改进灰色关联度和 IOWHA 算子的变权重区间数组合预测模型。并将变权重系数区间类型组合预测模型应用于区间数序列的预测,实例证明该模型是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interval Type Combination Prediction Model based on Improved Grey Correlation Degree IOWHA Operator
In order to improve the accuracy of interval number prediction, this paper proposes a new type of interval number combination prediction model based on improved grey correlation degree and IOWHA operator. Transform the interval number into the center and radius of equivalent information, introduce the IOWHA operator, use the interval number prediction accuracy as the inducing factor, and improve the grey correlation degree as the optimal criterion to construct a variable weight interval type combination prediction model based on the improved grey correlation degree and IOWHA operator. And the variable weight coefficient interval type combination prediction model is applied to the prediction of interval number sequences, and the example proves that the model is effective.
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