| 基于重构相空间FLS-SVM的电力系统混沌预测模型 |
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| 引用本文： | 蒋强,肖建,郑高,周文卫,王万岗.基于重构相空间FLS-SVM的电力系统混沌预测模型[J].信息与控制,2011,40(2). |
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| 作者姓名： | 蒋强 肖建 郑高 周文卫 王万岗 |
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| 作者单位： | 1. 西南交通大学电气工程学院,四川成都610031;乐山师范学院物理与电子工程学院,四川乐山614000
2. 西南交通大学电气工程学院,四川成都,610031 |
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| 基金项目： | 国家自然科学基金资助项目，四川省教育厅青年基金资助项目 |
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| 摘 要： | 研究电力系统混沌预测以及预测中超参数难以调整的问题,采用基于重构相空间的模糊最小二乘支持向量机(RFLS-SVM)方法进行算法改进.结合Takens嵌入维理论重构数据相空间,并对电力系统混沌状态进行预测,预测精度得到了进一步提高.并研究了RFLS-SVM核参数调整的方法,得到了一般性结论.通过数字仿真实验证明了该方法是有效的.
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| 关 键 词： | 非线性系统 混沌预测 最小二乘支持向量机 重构相空间 模糊 |
Power System Chaos Prediction Model Based on FLS-SVM via Reconstructed Phase Space |
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| JIANG Qiang,XIAO Jian,ZHENG Gao,ZHOU Wenwei,WANG Wangang.Power System Chaos Prediction Model Based on FLS-SVM via Reconstructed Phase Space[J].Information and Control,2011,40(2). |
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| Authors: | JIANG Qiang XIAO Jian ZHENG Gao ZHOU Wenwei WANG Wangang |
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| Affiliation: | JIANG Qiang~(1,2),XIAO Jian~1,ZHENG Gao~1,ZHOU Wenwei~1,WANG Wangang~1 (1.School of Electrical Engineering,Southwest Jjiaotong University,Chengdu 610031,China,2.School of Physics and Electric Engineering,Leshan Teachers College,Leshan 614000,China) |
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| Abstract: | Chaos forecasting of power system and the difficulty in super parameters adjustment are studied.Fuzzy least square support vector machine method based on space reconstruction(RFLS-SVM) is adopted to improve the algorithm. Data space is reconstructed based on Takens embedding theorem,and the chaotic state of power system is forecasted and the forecasting precision is improved.And also RFLS-SVM kernel parameters adjustment method is studied to get a general conclusion.Numerical simulation results show that th... |
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| Keywords: | nonlinear system chaos prediction LS-SVM(least square-support vector machine) reconstructed phase space fuzzy |
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