| 基于加权精度的ε-SVR组合参数优化 |
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| 引用本文： | 孙林凯,金家善,耿俊豹.基于加权精度的ε-SVR组合参数优化[J].系统工程与电子技术,2011,33(8). |
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| 作者姓名： | 孙林凯 金家善 耿俊豹 |
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| 作者单位： | 海军工程大学船舶与动力学院动力工程系,湖北武汉,430033 |
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| 基金项目： | 中国博士后科学基金(20080431380)资助课题 |
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| 摘 要： | 针对支持向量机参数的选取还没有一套完整的理论支撑,提出以加权精度来评价某一组参数的预测效果。通过循环交叉验证和全局变步长的方法,对最优参数进行搜索。考虑参数间的相互影响,研究参数的组合形式对精度的影响,确定参数的最优组合形式。实例分析表明,参数的最优组合能够提高支持向量机对设备费用的预测精度。
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| 关 键 词： | 费用预测 循环交叉验证 ε-支持向量回归机 最优参数 核函数 |
Combined parameter optimization for ε-SVR based on weighted accuracy |
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| SUN Lin-kai,JIN Jia-shan,GENG Jun-bao.Combined parameter optimization for ε-SVR based on weighted accuracy[J].System Engineering and Electronics,2011,33(8). |
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| Authors: | SUN Lin-kai JIN Jia-shan GENG Jun-bao |
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| Institution: | SUN Lin-kai,JIN Jia-shan,GENG Jun-bao(Department of Power Engineering,School of Naval Architecture & Power,Naval University of Engineering,Wuhan 430033,China) |
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| Abstract: | Aiming at the lack of integrity theories for choosing the parameters of the support vector regression machine(SVR),the combination accuracy is proposed to evaluate the estimated effect.The methods of circulation crisscross verification and variable step length are used to search the optimal parameters.The interaction of the parameters is considered.This paper researches the influence of the combined form of parameters on the estimated accuracy,and assures the optimized combined form of the parameters.The re... |
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