| 公路旅游客流量预测的支持向量回归模型 |
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| 引用本文： | 颜七笙,王士同. 公路旅游客流量预测的支持向量回归模型[J]. 计算机工程与应用, 2011, 47(9): 233-235. DOI: 10.3778/j.issn.1002-8331.2011.09.067 |
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| 作者姓名： | 颜七笙 王士同 |
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| 作者单位： | 1.江南大学 信息工程学院，江苏 无锡 214122 2.东华理工大学 数学与信息科学学院，江西 抚州 344000 |
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| 摘 要： | 介绍了基于统计学习理论的支持向量机回归原理，为解决公路旅游客流量预测建模中的小样本问题，实现对公路旅游客流量的快速准确预测，提出了基于支持向量机回归模型的公路旅游客流量预测方法，给出了参数优化选取算法。仿真实验表明，该方法具有比神经网络等方法更好的预测精度。说明支持向量回归方法用于公路旅游客流量预测是可行有效的。
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| 关 键 词： | 支持向量机 公路旅游客流量 神经网络 预测 |
| 修稿时间： | |
Support vector regression model for highway traveling passenger volume forecasting |
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| YAN Qisheng,WANG Shitong. Support vector regression model for highway traveling passenger volume forecasting[J]. Computer Engineering and Applications, 2011, 47(9): 233-235. DOI: 10.3778/j.issn.1002-8331.2011.09.067 |
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| Authors: | YAN Qisheng WANG Shitong |
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| Affiliation: | 1.School of Information Engineering，Jiangnan University，Wuxi，Jiangsu 214122，China 2.School of Mathematics & Information Science，East China Institute of Technology，Fuzhou，Jiangxi 344000，China |
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| Abstract: | The regression principle of Support Vector Machines（SVM） based on the statistic learning theory is introduced.To solve the problem of few training samples in modeling the prediction for highway traveling passenger volume,the method of modeling the highway traveling passenger volume based on the Support Vector machine Regression（SVR） model is presented.This algorithm is investigated to select the parameters of SVR model.A simulation example is taken to demonstrate correctness and effectiveness of the proposed approach.The result shows that the model and algorithm proposed possess convenience,objectivity and can get higher prediction precision than that of BP neural network. |
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| Keywords: | Support Vector Machines（SVM） highway traveling passenger volume neural network prediction |
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