[1]林屹,严洪森,周博.基于多维泰勒网的自适应混沌时间序列多步预测[J].东南大学学报(自然科学版),2015,45(2):281-288.[doi:10.3969/j.issn.1001-0505.2015.02.016]
 Lin Yi,Yan Hongsen,Zhou Bo.Adaptive multi-step prediction of chaotic time series based on multi-dimensional Taylor network[J].Journal of Southeast University (Natural Science Edition),2015,45(2):281-288.[doi:10.3969/j.issn.1001-0505.2015.02.016]
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基于多维泰勒网的自适应混沌时间序列多步预测()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
45
期数:
2015年第2期
页码:
281-288
栏目:
计算机科学与工程
出版日期:
2015-03-20

文章信息/Info

Title:
Adaptive multi-step prediction of chaotic time series based on multi-dimensional Taylor network
作者:
林屹123严洪森12周博12
1东南大学自动化学院, 南京210096; 2东南大学复杂工程系统测量与控制教育部重点实验室, 南京210096; 3 南京信息工程大学信息与控制学院, 南京210044
Author(s):
Lin Yi123 Yan Hongsen12 Zhou Bo12
1School of Automation, Southeast University, Nanjing 210096, China
2Key Laboratory of Measurement and Control of CSE of Ministry of Education, Southeast University, Nanjing 210096, China
3College of Information and Control, Nanjing University of Information Science and Technology, Nanjing 210044, China
关键词:
混沌时间序列 多维泰勒网 预测
Keywords:
chaotic time series multi-dimensional Taylor network prediction
分类号:
TP391
DOI:
10.3969/j.issn.1001-0505.2015.02.016
摘要:
提出了一种新的混沌时间序列预测方法——多维泰勒网方法.该方法不以相空间重构方法中嵌入维数和时间延迟这两个关键参数的选取为前提,无需系统的先验知识和机理,仅根据已知的时间序列样本,通过多维泰勒网模型获得n元一阶多项式差分方程组,进而得到能反映非线性系统动力学特性的多维泰勒网动态模型.在此基础上提出了基于多维泰勒网的自适应多步预测方法,通过数据窗口的滑动自适应建模,实现对混沌时间序列的多步预测. 将该方法应用于Lorenz混沌时间序列的一步和多步预测,均方误差分别达到2.56×10-5和2.76×10-3.仿真结果表明,该方法可以对混沌时间进行有效预测,且具有较高的预测精度.
Abstract:
A new chaotic time series prediction method, the method based on multi-dimensional Taylor network, is proposed. In this method it is unnecessary to choose the embedding dimension and delay time which are referred to as two key parameters in the process of phase-space reconstruction. Without prior knowledge and mechanism of the system, the first order n-variables polynomial difference equations can be obtained by the multi-dimensional Taylor network according to the known samples of the time series. Thus, the multi-dimensional Taylor network dynamics model is obtained, which can describe the dynamic characteristics of the nonlinear system. On this basis, an adaptive multi-step prediction method based on the multi-dimensional Taylor network is presented. The adaptive model realizes the multi-step prediction of chaotic time series by sliding the data window. Then the method is applied to single step and multi-step prediction of the Lorenz chaotic time series and the mean square errors are 2.56×10-5and 2.76×10-3, respectively. The simulation results indicate that the new method is valid in chaotic time series prediction with better predictive accuracy.

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备注/Memo

备注/Memo:
收稿日期: 2014-09-29.
作者简介: 林屹(1977—),女,博士生,讲师;严洪森(联系人),男,博士,教授,博士生导师,hsyan@seu.edu.cn.
基金项目: 国家自然科学基金重点资助项目(60934008)、中央高校基本科研业务费专项资金资助项目(2242014K10031).
引用本文: 林屹,严洪森,周博.基于多维泰勒网的自适应混沌时间序列多步预测[J].东南大学学报:自然科学版,2015,45(2):281-288. [doi:10.3969/j.issn.1001-0505.2015.02.016]
更新日期/Last Update: 2015-03-20