| LS-SVM的参数优选及铁路客运市场预测 |
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| 引用本文： | 周辉仁,郑丕谔.LS-SVM的参数优选及铁路客运市场预测[J].计算机工程与应用,2007,43(30):206-208. |
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| 作者姓名： | 周辉仁 郑丕谔 |
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| 作者单位： | 天津大学,系统工程研究所,天津,300072 |
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| 摘 要： | 提出通过建立验证性能指标用遗传算法优化最小二乘支持向量机的有关参数并进行时间序列预测。将最小二乘支持向量机以铁路客运市场数据进行训练和测试,并与传统的BP网络预测模型相比较,结果证明,该模型的预测精确度是令人满意的,提出的方法是可行的。
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| 关 键 词： | 最小二乘支持向量机 遗传算法 参数优化 时间序列预测 |
| 文章编号： | 1002-8331（2007）30-0206-03 |
| 修稿时间： | 2007-03 |
Method for selecting parameters of LS-SVM and forecasting market of railway passenger traffic |
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| ZHOU Hui-ren,ZHENG Pie.Method for selecting parameters of LS-SVM and forecasting market of railway passenger traffic[J].Computer Engineering and Applications,2007,43(30):206-208. |
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| Authors: | ZHOU Hui-ren ZHENG Pie |
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| Affiliation: | Institute of Systems Engineering,Tianjin University,Tianjin 300072, China |
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| Abstract: | In Least Squares Support Vector Machines(LS-SVM),a least squares cost function is proposed so as to obtain a linear set of equations in dual space.Through GA,hyper-parameters selection can be solved.The model is then used to forecast the market of railway passenger traffic.It is shown that the hierarchical genetic algorithm proposed is simple and effective. |
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| Keywords: | Least Squares Support Vector Machines(LS-SVM) Genetic Algorithm(GA) optimization of hyper-parameters time series prediction |
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