| 改进的LS—SVM算法及在交通流量预测上的应用 |
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| 引用本文： | 张朝元,陈丽.改进的LS—SVM算法及在交通流量预测上的应用[J].昆明理工大学学报(理工版),2008,33(6). |
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| 作者姓名： | 张朝元 陈丽 |
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| 作者单位： | 1. 大理学院数学与计算机学院,云南,大理,671003
2. 大理学院物理与电子信息学院,云南,大理,671003 |
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| 基金项目： | 大理学院科研基金资助项目
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| 摘 要： | 对标准的LS-SVM算法进行了改进,得到一种新的学习算法.这种新的学习算法不仅能减少计算的复杂性,提高学习速度;同时能提高函数估计的精确度.将改进的LS-SVM算法应用于交通流量的预测,同时与传统的多元线性回归及支持向量机方法进行比较,结果表明改进的LS-SVM方法具有较高的预测精度,且实验取得了较好效果.
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| 关 键 词： | SVM法 LS-SVM法 多元线性回归 交通流量 预测 |
Improved Algorithm of LS-SVM and Its Application to Traffic Flow Prediction |
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| ZHANG Chao-yuan,CHEN Li.Improved Algorithm of LS-SVM and Its Application to Traffic Flow Prediction[J].Journal of Kunming University of Science and Technology(Natural Science Edition),2008,33(6). |
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| Authors: | ZHANG Chao-yuan CHEN Li |
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| Affiliation: | ZHANG Chao-yuan1,CHEN Li2 |
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| Abstract: | Based on the traditional least squares support vector machine for function estimation,an improved algorithm of LS-SVM is presented in this paper.The proposed method can reduce the computation complexity and increase the learning speed.The accuracy of estimation is also improved.Through its application to traffic flow prediction and through comparison with the traditional multiple linear regression and support vector machine,this method is proved to be more effective and precise. |
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| Keywords: | SVM LS-VSM multiple linear regression traffic flow prediction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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