| 二维色谱柱效的支持向量回归预测 |
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| 引用本文： | 蔡从中,温玉锋,裴军芳,朱星键.二维色谱柱效的支持向量回归预测[J].分析化学,2009,37(6). |
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| 作者姓名： | 蔡从中 温玉锋 裴军芳 朱星键 |
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| 作者单位： | 重庆大学应用物理系,重庆,400044 |
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| 基金项目： | 教育部新世纪优秀人才支持计划，教育部留学回国人员科研启动基金，重庆市自然科学基金 |
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| 摘 要： | 以有效塔板数作为二维色谱的柱效指标,根据二维色谱在不同影响因素(包括预柱柱温、主柱柱温、柱间压差和主柱间的放空量)下的有效塔板数实测数据集,应用基于粒子群算法(PSO)寻优的支持向量回归(SVR)方法,建立了二维色谱柱效的SVR预测模型,并与BP神经网络(BPNN)模型进行了比较.结果表明:基于相同的训练样本和检验样本,二维色谱的SVR模型的平均绝对百分误差(MAPE, 13.3%)比其BPNN模型的MAPE小4%;增加训练样本数有助于提高支持向量回归(SVR)模型的泛化性能;基于留一交叉验证法(LOOCV)的SVR模型预测的平均绝对误差(MAE, 196.79 m-1)和MAPE(1.6%)均为最小,明显优于BPNN模型(2397.98 m-1, 17.3%)或SVR模型(1849.95 m-1, 13.3%)的预测效果.因此,SVR是一种预测二维色谱柱效的有效方法.
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| 关 键 词： | 二维色谱 柱效 支持向量回归 粒子群算法 回归分析 预测 |
Column Efficiency Prediction of Two-Dimensional Chromatography Based on Support Vector Regression |
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| CAI Cong-Zhong,WEN Yu-Feng,PEI Jun-Fang,ZHU Xing-Jian.Column Efficiency Prediction of Two-Dimensional Chromatography Based on Support Vector Regression[J].Chinese Journal of Analytical Chemistry,2009,37(6). |
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| Authors: | CAI Cong-Zhong WEN Yu-Feng PEI Jun-Fang ZHU Xing-Jian |
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| Institution: | Department of Applied Physics;Chongqing University;Chongqing 400044 |
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| Abstract: | The effective plate number represents the column efficiency of two-dimensional chromatography.Based on the experimental dataset,the support vector regression(SVR) approach combined with particle swarm optimization(PSO) for its parameter optimization was proposed to establish a SVR model for estimating the column efficiency of two dimensional chromatography under different factors,which consisted of temperature of pre-column,temperature of main column,pressure difference between the columns and the vent rate... |
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| Keywords: | Two-dimensional chromatography column efficiency support vector regression particle swarm optimization regression analysis prediction |
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