| 基于CPSO和SVM的混沌时间序列预测 |
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| 引用本文： | 郭良栋,田江,丛晓东.基于CPSO和SVM的混沌时间序列预测[J].鞍山科技大学学报,2009,32(6):561-565,570. |
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| 作者姓名： | 郭良栋 田江 丛晓东 |
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| 作者单位： | [1]辽宁科技大学理学院,辽宁鞍山114051 [2]大连理工大学电信学院,辽宁大连116114 [3]广东志高空调有限公司,广东佛山528244 |
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| 摘 要： | 提出了一种改进的支持向量机（SVM）混沌时间序列预测精度的方法。对于模型参数估计,引入混沌粒子群优化算法（CPSO）实现全局寻优,利用支持向量回归实现非线性系统的建模和预测。对Mackey-Glass混沌时间序列进行了预测实验的结果表明,本文方法能对Mackey-Glass混沌时间序列进行准确预测。
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| 关 键 词： | 混沌时间序列 混沌粒子群优化 支持向量机 |
Prediction of chaotic time series based on CPSO and SVM |
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| GUO Liang-dong,TIAN Jiang,CONG Xiao-dong.Prediction of chaotic time series based on CPSO and SVM[J].Journal of Anshan University of Science and Technology,2009,32(6):561-565,570. |
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| Authors: | GUO Liang-dong TIAN Jiang CONG Xiao-dong |
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| Institution: | GUO Liang-dong1,TIAN Jiang2,CONG Xiao-dong3 (1.School of Science,University of Science , Technology Liaoning,Anshan 114051,China,2.School of Electronic , Information Engineering,Dalian University of Technology,Dalian,116114,3.Guangdong Zhigao Air Conditioner Co.,Ltd,Feshan,528244,China) |
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| Abstract: | Based on chaos particle swarm optimization(CPSO) algorithm and support vector machine(SVM),an advanced approach is presented to enhance the ability of time series prediction.PSO algorithm with chaos perturbation is utilized to reach the global optimum of SVM parameters estimation,model and prediction of nonlinear systems are relized by using support vector regression.Simulations on the chaotic Mackey-Glass time series prediction are performed.The results show that this method provides accuracy and effective... |
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| Keywords: | chaotic time series chaos particle swarm optimization support vector machine |
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