GM(1, 1) model for interval grey number based on genetic algorithm

被引：0

作者：

Wu L.-Y. ^{[1
]}

Wu Z.-P. ^{[1
]}

Qi Y.-J. ^{[1
]}

机构：

[1] Faculty of Science and Technology, Communication University of China, Beijing

来源：

Kongzhi yu Juece/Control and Decision | 2019年 / 34卷 / 02期

关键词：

Genetic algorithm; GM(1; 1); Grey interval prediction model; Grey system theory; Optimize;

D O I：

10.13195/j.kzyjc.2017.1060

中图分类号：

学科分类号：

摘要：

In this paper, we use the genetic algorithm as a tool to optimize the parameter of the model based on grey number layers and grey number interval prediction. Firstly, the mean variable weight generating thoughts is used instead of the non-bias generator to obtain the real number from the interval grey number. Then the GM(1, 1) model is built according to the real number sequence. The optimal-operator is designed by minimizing the average relative error of the grey interval perdiction. The example simulation is given to illustrate that the average relative error and prediction error of the proposed model are significantly lower than that of other models, which shows the effectiveness and feasibility of the proposed model. © 2019, Editorial Office of Control and Decision. All right reserved.

引用

页码：445 / 448

页数：3

共 7 条

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