[1]龙科军,李超群,毛学军,等.高速公路雾天能见度预测方法[J].徐州工程学院学报(自然科学版),2017,(1):31-37.
 LONG Kejun,LI Chaoqun,MAO Xuejun,et al.Forecasting Method of Highway Visibility in Foggy Weather[J].Journal of Xuzhou Institute of Technology(Natural Sciences Edition),2017,(1):31-37.
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高速公路雾天能见度预测方法()
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《徐州工程学院学报》(自然科学版)[ISSN:1674-358X/CN:32-1789/N]

卷:
期数:
2017年第1期
页码:
31-37
栏目:
专家特稿
出版日期:
2017-02-28

文章信息/Info

Title:
Forecasting Method of Highway Visibility in Foggy Weather
文章编号:
1674-358X(2017)01-0031-07
作者:
龙科军1李超群1毛学军2胡玉婷3
1.长沙理工大学 交通运输工程学院,湖南 长沙 410004; 2.江西公路开发总公司,江西 南昌 330000; 3.江西省交通工程集团有限公司,江西 南昌 330000
Author(s):
LONG Kejun1LI Chaoqun1MAO Xuejun2HU Yuting3
1.School of Traffic and Transportation, Changsha University of Science and Technology, Changsha 410004,China; 2.Jiangxi Road Development Corporation,Nanchang 330000,China; 3.Jiangxi Traffic Engineering Group Co., Ltd, Nanchang 330000,China
关键词:
高速公路 雾天 能见度 BP神经网络 支持向量机
Keywords:
highway foggy weather visibility BP neural network support vector machine
分类号:
U491
文献标志码:
A
摘要:
以多要素气象检测器采集的样本数据为基础,将温度、风速及湿度作为输入变量以及雾天能见度作为输出变量,分别采用三层结构BP神经网络和支持向量机非线性回归预测方法,建立雾天能见度的预测模型; 将预测结果与实际数据进行对比分析的结果表明:BP神经网络和支持向量机均能较好地预测雾天能见度,其中BP神经网络和支持向量机模型预测值与实际值的相关性分别为0.895和0.978.支持向量机预测结果的误差更稳定,因而更适于处理非线性小样数据.
Abstract:
Taking temperature,wind speed and humidity as input variables and fog visibility as output variables,the forecasting model of highway visibility in foggy weather was established based on the sample data collected by multi-element meteorological detector with the three-layer BP neural network and nonlinear regression of support vector machine.The results showed that the visibility of the fog can be forecast by the BP neural network and the support vector machine,whose correlation values between the predictive and the actual were 0.895 and 0.978.The error of support vector machine prediction is more stable,so it is more suitable for dealing with small sample,nonlinear, high dimension and local minima.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2016-07-06 基金项目:江西省交通运输科技计划项目(2013C0008); 长沙理工大学研究生科研创新项目 作者简介:龙科军(1974-),男,教授,博士,硕士生导师,主要从事道路交通运输研究.
更新日期/Last Update: 1900-01-01