| 基于SCE-UA支持向量机的短期电力负荷预测模型研究 |
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| 引用本文： | 李刚,程春田,曾筠,林剑艺.基于SCE-UA支持向量机的短期电力负荷预测模型研究[J].大连理工大学学报,2011,51(2):263-268. |
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| 作者姓名： | 李刚 程春田 曾筠 林剑艺 |
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| 作者单位： | 大连理工大学水电与水信息研究所; |
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| 基金项目： | 国家自然科学基金资助项目(50909011); “九七三”国家重点基础研究发展计划资助项目(2009CB226111) |
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| 摘 要： | 支持向量机(support vector machine,SVM)作为一种新颖的机器学习方法已成功应用于短期电力负荷预测,然而应用研究发现SVM算法性能参数的设置将直接影响负荷预测的精度.为此在对SVM参数性能分析的基础上,提出了SCE-UA(shuffled complex evolution University ...
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| 关 键 词： | 负荷预测 支持向量机 SCE-UA 相似日 |
Research on short-term electricity load forecasting model using support vector machine based on SCE-UA algorithm |
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| LI Gang,CHENG Chuntian,ZENG Yun,LIN Jianyi.Research on short-term electricity load forecasting model using support vector machine based on SCE-UA algorithm[J].Journal of Dalian University of Technology,2011,51(2):263-268. |
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| Authors: | LI Gang CHENG Chuntian ZENG Yun LIN Jianyi |
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| Institution: | LI Gang*,CHENG Chun-tian,ZENG Yun,LIN Jian-yi Institute of Hydropower & Hydroinformatics,Dalian University of Technology,Dalian 116024,China |
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| Abstract: | Support vector machine(SVM) is a novel type of learning machine,which has been successfully applied to short-term electricity load forecasting.However,its application indicates that how to confirm the parameters of SVM algorithm directly affects forecasting precision.On the basis of analyzing the parameter performance of SVM for regression estimation,a short-term electricity load forecasting model SCE-UA(shuffled complex evolution-University of Arizona) based on SVM is presented.In the process of establishi... |
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| Keywords: | load forecasting SVM SCE-UA similar day |
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