| SVM算法应用于大气污染时间序列预测 |
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| 引用本文： | 倪振威,宋道柱,朱成龙,王 强,李 洁.SVM算法应用于大气污染时间序列预测[J].硅谷,2014(8):50-51. |
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| 作者姓名： | 倪振威 宋道柱 朱成龙 王 强 李 洁 |
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| 作者单位： | [1]徐州工程学院环境工程学院,江苏徐州221111 [2]徐州工程学院机电工程学院,江苏徐州221000 [3]徐州工程学院信电工程学院,江苏徐州221111 [4]徐州工程学院人文学院,江苏徐州221111 |
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| 摘 要： | 支持向量机(SVM)的在大气污染预测中显示出良好的非线性回归预测性能,本文通过建立基于该算法的时间序列模型,通过选取最优超平面,利用RBF核函数来解决在大气预测中线性不可分的问题。并取得了很高的预测精度结果 ,为大气回归预测方面的问题研究提供了一种崭新的思路。
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| 关 键 词： | 向量机 RBF核函数 预测 |
SVM algorithm is applied to time series prediction of atmospheric pollution |
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| Ni Zhen-wei;Song Dao-zhu;Zhu Cheng-long;Wang Qiang;Li Jie.SVM algorithm is applied to time series prediction of atmospheric pollution[J].Silicon Valley,2014(8):50-51. |
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| Authors: | Ni Zhen-wei;Song Dao-zhu;Zhu Cheng-long;Wang Qiang;Li Jie |
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| Affiliation: | Ni Zhen-wei;Song Dao-zhu;Zhu Cheng-long;Wang Qiang;Li Jie (IXuzhou Institute of Environmental Engineering Jiangsu Xuzhou 2211112 Xuzhou Institute of Mechanical and Electrical Engineering Jiangsu Xuzhou 221111 ;3 Xuzhou Institute of Information and Electrical Engineering College Jiangsu Xuzhou 221111;4 Xuzhou Institute of Humanities Jiangsu Xuzhou 221111) |
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| Abstract: | Support Vector Machines 0 in air pollunon torecasung nonlinear regression showed good predictive performance, this paper established time series model based on the algorithm, by selecting optimal hyperplane, the use of nuclear functions to solve linear prediction in the atmosphere can not be separated problems. And achieved a high prediction accuracy results for the atmospheric research questions regression prediction provides a new way of thinking. |
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| Keywords: | Vector machines kernel functioa forecast |
| 本文献已被 CNKI 维普 等数据库收录！ |
