Network delay prediction based on model of modified ensemble empirical mode decomposition-permutation entropy and cuckoo search-wavelet neural network

被引：2
|
作者：
Shi W. [1 ]
Guo M. [1 ]
机构：
[1] College of Electrical and Information Engineering, Dalian Jiaotong University, Dalian
来源：
| 1600年 / Chinese Institute of Electronics卷 / 42期
关键词：
Cuckoo search (CS); Delay prediction; Modified ensemble empirical mode decomposition (MEEMD); Networked control system; Permutation entropy; Wavelet neural network (WNN);
D O I：
10.3969/j.issn.1001-506X.2020.01.25
中图分类号：
学科分类号：
摘要：
Aiming at the characteristics of randomness, instability and nonlinear induced delay of networked control system, a delay prediction algorithm of modified ensemble empirical mode decomposition-permutation entropy (MEEMD-PE) and wavelet neural network (WNN) optimized by cuckoo search (CS) is proposed. Firstly, MEEMD is used to decompose the original delay sequence, then the permutation entropy values of each sub sequence are calculated and recombination of new subsequences to reduce the non-stationary characteristics of the delay sequence and amount of calculation. And then predict the new subsequences by the WNN optimized by the CS algorithm. The final results of network delay are calculated by superimposing the prediction of the submodels. Simulation results show that the method has the advantages of better prediction accuracy, reflecting the overall trend of the delay sequence, and effectively reducing the impact of outliers. © 2020, Editorial Office of Systems Engineering and Electronics. All right reserved.
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页码：184 / 190
页数：6
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