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| 基于最大互信息的混沌时间序列多步预测 | |
| 引用本文： | 张春涛,刘学飞,向瑞银,刘金魁,郭 皎.基于最大互信息的混沌时间序列多步预测[J].控制与决策,2012,27(6):941-944. |
| 作者姓名： | 张春涛 刘学飞 向瑞银 刘金魁 郭 皎 |
| 作者单位： | 重庆三峡学院数学与统计学院,重庆万州,404100 |
| 基金项目： | 重庆市教委科技项目，东南大学基本科研业务费“创新基金”项目，重庆三峡学院重点项目 |
| 摘 要： | 针对混沌时间序列的多步预测,提出了基于最大互信息（MMI）的建模方法.首先建立时间延迟、嵌入维数和预测步长在相空间的最大信息量模型;然后利用遗传算法求解并确定混沌时间序列的最佳预测结构;最后对Mackey-Glass系统和月太阳黑子的仿真实验表明,MMI可以确定更好的预测结构,提高了混沌时间序列的预测精度. |
| 关 键 词： | 混沌时间序列 互信息 预测结构 神经网络预测 |
| 收稿时间： | 2010/11/18 0:00:00 |
| 修稿时间： | 2011/1/21 0:00:00 |
Multi-step-prediction of chaotic time series based on maximized mutual information |
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| ZHANG Chun-tao,LIU Xue-fei,XIANG Rui-yin,LIU Jin-kui,GUO Jiao.Multi-step-prediction of chaotic time series based on maximized mutual information[J].Control and Decision,2012,27(6):941-944. |
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| Authors: | ZHANG Chun-tao LIU Xue-fei XIANG Rui-yin LIU Jin-kui GUO Jiao |
| Affiliation: | (College of Mathematic and Computer Science,Chongqing Three Gorges University,Wanzhou 404100,China.) |
| Abstract: | For the multi-step-prediction of chaotic time series,a modeling method based on maximized the mutual information(MMI) is proposed.Firstly,maximize information model in phase space with delay time,embedding dimension and prediction step is established.Then this model can be solved by using generation algorithm(GA),which determines the better prediction structure of chaotic time series.Finally,simulations of the Mackey-Glass system and monthly sunspot show that MMI can determine the better prediction structure and improve the prediction accuracy of chaotic time series. |
| Keywords: | chaotic time series mutual information prediction structure neural network prediction |
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