| 支持向量机在钻井工程数据拟合中的应用 |
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| 引用本文： | 陈华,范宜仁,邓少贵.支持向量机在钻井工程数据拟合中的应用[J].计算机工程与应用,2006,42(21):178-179,213. |
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| 作者姓名： | 陈华 范宜仁 邓少贵 |
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| 作者单位： | 中国石油大学(华东)山东,东营,257061 |
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| 摘 要： | 支持向量机(SVM)是近年来发展起来的一种通用的机器学习方法,在小样本数据的拟合中已获得了很好的效果。对于常见的支持向量回归机方法:ε-支持向量回归机和最小二乘支持向量回归机进行了归纳总结,并给出了一具体应用案例。
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| 关 键 词： | 支持向量机 拟合 ε-支持向量回归机 最小二乘支持向量回归机 |
| 文章编号： | 1002-8331-（2006）21-0178-02 |
| 收稿时间： | 2006-04-01 |
| 修稿时间： | 2006-04-01 |
Application of Support Vector Machine in the Data Fitting of Drill Well Engineering |
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| Chen Hua,Fan Yiren,Deng Shaogui.Application of Support Vector Machine in the Data Fitting of Drill Well Engineering[J].Computer Engineering and Applications,2006,42(21):178-179,213. |
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| Authors: | Chen Hua Fan Yiren Deng Shaogui |
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| Affiliation: | University of Petroleum China, Dongying, Shandong 257061 |
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| Abstract: | Support Vector Machine(SVM) is a general machine learning method in recent years,by which good results have been obtained in fitting of small samples.Summarize Support Vector Machine methods which are often applied:ε-Support Vector Regression and Least square Support Vector Regression,and illustrates a application case. |
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| Keywords: | Support Vector Machine fitting ε-Support Vector Regression Least Square Support Vector Regression |
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