基于相空间重构的Bernstein神经网络混沌序列预测

系统仿真学报 ›› 2016, Vol. 28 ›› Issue (4): 880-889.

基于相空间重构的Bernstein神经网络混沌序列预测

张宏立¹, 李瑞国¹, 范文慧²

1.新疆大学电气工程学院,新疆乌鲁木齐 830047;
2.清华大学自动化系,北京 100084

收稿日期:2014-11-18 修回日期:2015-04-22 出版日期:2016-04-08 发布日期:2020-07-02
作者简介:张宏立(1972-),男,湖南,博士,副教授,研究方向为混沌分析、系统辨识等;李瑞国(1986-),男,满族,河北,硕士生,研究方向为混沌理论与应用、模式识别等;范文慧(1966-),男,吉林,博士,教授,研究方向为协同仿真、协同优化等。
基金资助:
国家自然科学基金(61463047)

Bernstein Neural Network Chaotic Sequence Prediction Based on Phase Space Reconstruction

Zhang Hongli¹, Li Ruiguo¹, Fan Wenhui²

1. Department of Electrical Engineering, Xinjiang University, Urumqi 830047, China;
2. Department of Automation, Tsinghua University, Beijing 100084, China

Received:2014-11-18 Revised:2015-04-22 Online:2016-04-08 Published:2020-07-02

摘要/Abstract

摘要： 针对传统BP神经网络、RBF神经网络及AR模型预测精度不高、结构复杂,提出了相空间重构与Bernstein神经网络组合预测的新方法,并结合PSO算法进行组合预测模型的参数优化。分别以Sprott-J混沌系统和交通流系统为模型,利用自相关法和Cao方法相结合对混沌时间序列进行相空间重构;利用重构时间延迟相量及Bernstein神经网络建立预测模型,并与传统的BP神经网络、RBF神经网络及AR模型进行对比分析。仿真结果表明,相空间重构与Bernstein神经网络组合预测较传统模型结构简单、模拟效果好、预测精度高。

关键词: 相空间重构, Bernstein神经网络, PSO算法, 混沌时间序列预测

Abstract: In view of the low prediction accuracy and the complex structure of traditional BP neural network, RBF neural network and AR model, a new prediction method with the combination of phase space reconstruction and Bernstein neural network was proposed, and PSO algorithm was used for parameters optimization of combination forecast model. Taking Sprott-J chaotic system and traffic flow system as models respectively, the combination of autocorrelation and Cao method was used to reconstruct phase space of chaotic time sequence, the refactoring phasor of time delay and Bernstein neural network were used to establish the prediction model, and do comparative analysis with traditional BP neural network, RBF neural network and AR models. The simulation results show that the combination prediction of phase space reconstruction and Bernstein neural network has a simple structure and can get more preferable simulation effect and higher prediction accuracy.

Key words: phase space reconstruction, Bernstein neural network, PSO algorithm, chaotic time sequence prediction

中图分类号:

TP391.9

张宏立, 李瑞国, 范文慧. 基于相空间重构的Bernstein神经网络混沌序列预测[J]. 系统仿真学报, 2016, 28(4): 880-889.

Zhang Hongli, Li Ruiguo, Fan Wenhui. Bernstein Neural Network Chaotic Sequence Prediction Based on Phase Space Reconstruction[J]. Journal of System Simulation, 2016, 28(4): 880-889.

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