A Novel Grey Multi-Dimensional Taylor Network Scheme for Nonlinear Time Series Prediction in Industrial Systems

被引:0
|
作者
Li, Chenlong [1 ,2 ]
Ma, Xiaoshuang [3 ,4 ]
Yuan, Changshun [1 ]
Wang, Bingqiang [5 ]
Liu, Chen [6 ]
Wang, Feng [1 ,2 ]
Chen, Wenliang [1 ,2 ]
机构
[1] Beihang Univ, Hangzhou Innovat Inst, Hangzhou 310051, Peoples R China
[2] Beihang Univ, Sch Elect Informat Engn, Beijing 100191, Peoples R China
[3] Southeast Univ, Sch Instrument Sci & Engn, Nanjing 210096, Peoples R China
[4] Minist Educ, Key Lab Microinertial Instrument & Adv Nav Techno, Nanjing 210096, Peoples R China
[5] Shandong WEGO Med Robot Grp, Weihai 264209, Peoples R China
[6] RMIT Univ, Sch Engn, Melbourne, Vic 3001, Australia
来源
JOURNAL OF GREY SYSTEM | 2022年 / 34卷 / 02期
关键词
Multi-dimensional Taylor Network; Nonlinear Time Series Prediction; GM(1,1); Industrial Systems; NEURAL-NETWORKS; MODEL; GM(1,1); ARIMA;
D O I
暂无
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
A novel grey multi-dimensional Taylor network (MTN) scheme for nonlinear time series prediction in industrial systems is proposed in this paper. First, we construct the grey MTN model: 1) the GM(1,1) model is used to gain the prediction value and as a group of inputs for the MTN prediction model, which improves the prediction accuracy; 2) we take the MTN model as the prediction model and the conjugate gradient (CG) method as its learning algorithm. Second, the variational mode decomposition (VMD) method is used as data preprocessing for inputs of the prediction model, and the processed data are normalised. Finally, the actual prediction values are obtained by reverse normalization processing. Industrial examples are presented to verify the effectiveness of the proposed scheme. The experimental results show that the proposed prediction scheme is effective. Meanwhile, compared with other schemes, the proposed scheme improves the prediction accuracy and performance considerably.
引用
收藏
页码:88 / 107
页数:20
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