| 加权支持向量回归机及其在水质预测中的应用 |
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| 引用本文： | 徐红敏,王继广.加权支持向量回归机及其在水质预测中的应用[J].世界地质,2007,26(1):58-61. |
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| 作者姓名： | 徐红敏 王继广 |
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| 作者单位： | 1. 吉林大学地球探测与信息技术学院,长春130026;北京石油化工学院数理系,北京102617
2. 山东省地质调查研究院,济南250019 |
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| 摘 要： | 支持向量机是一种基于结构风险最小化原理的学习技术，也是一种新的具有很好泛化性能的回归方法。本文对用于回归估计的标准支持向量机加以改进，提出了一种新的用于回归估计的支持向量机学习算法，针对各样本重要性的差异，给各个样本的惩罚系数和误差要求赋予不同权重，并利用加权支持向量回归机的理论及其算法构建水质预测模型。实验结果表明，该方法对水质具有较好的预测效果。
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| 关 键 词： | 加权支持向量机 回归估计 水质预测 |
| 文章编号： | 1004-5589（2007）01-0058-04 |
| 修稿时间： | 2006-09-202006-12-26 |
Weighted support vector machine for regression and its application for prediction of water quality |
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| XU Hong-min,WANG Ji-guang.Weighted support vector machine for regression and its application for prediction of water quality[J].World Geology,2007,26(1):58-61. |
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| Authors: | XU Hong-min WANG Ji-guang |
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| Abstract: | Support vector machine is a learning technique based on the structural risk minimization principle as well as a new regression method with good generalization ability.On the basis of the normal support vector machine for regression estimation,a new learning algorithm is presented.According to its significant difference,the authors proposed the penalty coefficient and limitation in error for the every sample to different weighted value,and established the model of water quality prediction by using weighted support vector regression(SVR) theory and its algorithm.The experimental results show that it is an effective method for water quality prediction. |
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| Keywords: | weighted support vector machine regression estimation water quality prediction |
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