A multiperiod grey prediction model and its application

被引:3
|
作者
Luo, D. [1 ]
Zhang, G. Z. [1 ,2 ]
机构
[1] North China Univ Water Resources & Elect Power, Zhengzhou, Henan, Peoples R China
[2] Henan Univ Econ & Law, Zhengzhou, Henan, Peoples R China
关键词
Nonlinear sequences; multiperiod; grey model; empirical mode decomposition; Fourier series; DECOMPOSITION; CONSUMPTION; DEMAND;
D O I
10.3233/JIFS-202775
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The purpose of this paper is to solve the prediction problem of nonlinear sequences with multiperiodic features, and a multiperiod grey prediction model based on grey theory and Fourier series is established. For nonlinear sequences with both trend and periodic features, the empirical mode decomposition method is used to decompose the sequences into several periodic terms and a trend term; then, a grey model is used to fit the trend term, and the Fourier series method is used to fit the periodic terms. Finally, the optimization parameters of the model are solved with the objective of obtaining a minimum mean square error. The novel model is applied to research on the loss rate of agricultural droughts in Henan Province. The average absolute error and root mean square error of the empirical analysis are 0.3960 and 0.5086, respectively. The predicted results show that the novel model can effectively fit the loss rate sequence. Compared with other models, the novel model has higher prediction accuracy and is suitable for the prediction of multiperiod sequences.
引用
收藏
页码:11577 / 11586
页数:10
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