Chaotic time series prediction of power system by using optimized time spectrum neural network

被引：0
|
作者：
Lu Y. [1 ]
Wei D. [1 ]
机构：
[1] College of Electronic Engineering, Guangxi Normal University, Guilin
来源：
Zhendong yu Chongji/Journal of Vibration and Shock | 2023年 / 42卷 / 11期
关键词：
chaos; multivariate time series prediction; neural network; optimization algorithm; power system;
D O I：
10.13465/j.cnki.jvs.2023.11.019
中图分类号：
学科分类号：
摘要：
Power system is a strong coupling and multivariable system, and the prediction of its multivariate chaotic time series is a difficult problem at present. In this paper, a time spectrum neural network based on optimization is proposed for chaos prediction of power system. Firstly, the potential correlation layer is used to mine the potential correlation between multivariate time series, and then the time series are converted into frequency domain signals through the sequence conversion unit to learn their characteristics. Finally, a variety of algorithms are combined to optimize the model to achieve better prediction effect. Experimental results illustrated that the optimized time spectrum neural network can not only predict the multivariable chaos of power system, but also has higher prediction accuracy and stability than other baseline models. © 2023 Chinese Vibration Engineering Society. All rights reserved.
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页码：156 / 162
页数：6
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