[1]王建,邓卫,赵金宝.基于改进型贝叶斯组合模型的短时交通流量预测[J].东南大学学报(自然科学版),2012,42(1):162-167.[doi:10.3969/j.issn.1001-0505.2012.01.030]
 Wang Jian,Deng Wei,Zhao Jinbao.Short-term freeway traffic flow prediction based on improved Bayesian combined model[J].Journal of Southeast University (Natural Science Edition),2012,42(1):162-167.[doi:10.3969/j.issn.1001-0505.2012.01.030]
点击复制

基于改进型贝叶斯组合模型的短时交通流量预测()
分享到:

《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
42
期数:
2012年第1期
页码:
162-167
栏目:
交通运输工程
出版日期:
2012-01-18

文章信息/Info

Title:
Short-term freeway traffic flow prediction based on improved Bayesian combined model
作者:
王建邓卫赵金宝
(东南大学交通学院,南京 210096)
Author(s):
Wang JianDeng WeiZhao Jinbao
(School of Transportation, Southeast University, Nanjing 210096, China)
关键词:
贝叶斯组合模型交通流小波分析ARIMA算法BP神经网络
Keywords:
Bayesian combined model traffic flow wavelet analysis autoregressive integrated moving average algorithm back propagation neural network
分类号:
U491.1
DOI:
10.3969/j.issn.1001-0505.2012.01.030
摘要:
针对短时交通流量预测的难题,在传统贝叶斯组合模型进行改善的基础上,提出一种改进型贝叶斯组合模型.该模型只根据各基本预测模型当前时刻之前几个交通流量的预测表现,通过提出的分配算法实时更新组合模型中各个基本预测模型的权重,从而改善了传统贝叶斯组合模型权重计算迭代步长过长的缺陷,提高了贝叶斯组合模型对各个基本预测模型预测精度的灵敏性.通过对实地的交通流量的预测发现,基于改进型贝叶斯组合模型的预测精度不仅优于单一的预测方法,而且也优于传统的贝叶斯组合模型,从而证明了改进型贝叶斯组合模型有效提高预测的可靠性和具有一定的实用性.
Abstract:
To solve the problem of short-term traffic flow prediction, a new method called improved Bayesian combined model is put forward based on the improvement of the traditional Bayesian combined model. This method can update each basic prediction models’ weights only by its performance in the past several times. Thus the defect of over iteration steps for calculating the weights in traditional Bayesian combined model can be corrected. The improved Bayesian combined model is more sensitive to the accuracy of each basic prediction model. According to the performance of the practical traffic data prediction, the results of improved Bayesian combined model are not only better than the single prediction model, but also better than traditional Bayesian combined model. Consequently, it is regarded that the improved Bayesian combined model increases the credibility of the prediction, and is applicable for the real condition.

参考文献/References:

[1] Turochy R E.Enhancing short-term traffic forecasting with traffic condition information [J].Journal of Transportation Engineering,2006,132(6):469-474.
[2] Smith B L,Williams B M,Oswald R K.Comparison of parametric and nonparametric models for traffic flow forecasting [J].Transportation Research Part C:Emerging Technologies,2002,10(4):303-321.
[3] Castro-Neto M,Jeong Y-S,Jeong M-K,et al.Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions [J].Expert Systems with Applications,2009,36(3):6164-6173.
[4] Hong W C,Dong Y C,Zheng F F,et al.Forecasting urban traffic flow by SVR with continuous ACO [J].Applied Mathematical Modelling,2011,35(3):1282-1291.
[5] 张晓利,贺国光.基于主成分分析和组合神经网络的短时交通流预测方法[J].系统工程理论与实践,2007,27(8):167-171.
  Zhang Xiaoli,He Guoguang.The forecasting approach for short-term traffic flow based on principal component analysis and combined NN[J].Systems Engineering—Theory &Practice,2007,27(8):167-171.(in Chinese)
[6] Vlahogianni E I,Karlaftis M G,Golias J C.Optimized and meta-optimized neural networks for short-term traffic flow prediction:a genetic approach [J].Transportation Research Part C:Emerging Technologies,2005,13(3):211-234.
[7] Okutani I,Stephanedes Y J.Dynamic prediction of traffic volume through Kalman filtering theory [J].Transportation Research Part B:Methodological,1984,18(1):1-11.
[8] 聂佩林,余志,何兆成.基于约束卡尔曼滤波的短时交通流量组合预测模型[J].交通运输工程学报,2008,8(5):86-90.
  Nie Peilin,Yu Zhi,He Zhaocheng.Constrained Kalman filter combined predictor for short-term traffic flow [J].Journal of Traffic and Transportation Engineering,2008,8(5):86-90.(in Chinese)
[9] 沈国江,王啸虎,孔祥杰.短时交通流量智能组合预测模型及应用[J].系统工程理论与实践,2011,31(3):511-518.
  Shen Guojiang,Wang Xiaohu,Kong Xiangjie.Short-term traffic volume intelligent hybrid forecasting model and its application [J].Systems Engineering—Theory &Practice,2011,31(3):511-518.(in Chinese)
[10] 郑为中,史其信.基于贝叶斯组合模型的短期交通量预测研究[J].中国公路学报,2005,18(1):85-89.
  Zhen Weizhong,Shi Qixin.Study of short-term freeway traffic flow prediction based on Bayesian combined model [J].China Journal of Highway and Transport,2005,18(1):85-89.(in Chinese)
[11] Petridis V,Kehagias A,Petrou L,et al.A Bayesian multiple models combination method for time series prediction [J].Journal of Intelligent and Robotic Systems,2001,31(1/2/3):69-89.
[12] 窦慧丽,刘好德,吴志周,等.基于小波分析和ARIMA模型的交通流预测方法[J].同济大学学报,2009,37(4):486-494.
  Dou Huili,Liu Haode,Wu Zhizhou,et al.Study of traffic flow prediction based on wavelet analysis and autoregressive integrated moving average model [J].Journal of Tongji University,2009,37(4):486-494.(in Chinese)
[13] Cao J C,Cao S H.Study of forecasting solar irradiance using neural networks with preprocessing sample data by wavelet analysis[J].Energy,2006,31(15):3435-3455.
[14] Hanbay D,Turkoglu I,Demir Y.Prediction of wastewater treatment plant performance based on wavelet packet decomposition and neural networks [J].Expert Systems with Applications,2008,34(2):1038-1043.
[15] 冯金巧,杨兆升,孙占全,等.基于小波分析的交通参数组合预测方法[J].吉林大学学报:工学版,2010,40(5):1120-1124.
  Feng Jinqiao,Yang Zhaosheng,Sun Zhanquan,et al.Combined method for traffic parameter prediction based on wavelet analysis [J].Journal o f Jilin University:Engineering and Technology Edition,2010,40(5):1120-1124.(in Chinese)

相似文献/References:

[1]常玉林,王炜,邓卫,等.双车道公路车头时距分布模型研究及应用[J].东南大学学报(自然科学版),1999,29(6):108.[doi:10.3969/j.issn.1001-0505.1999.06.024]
 Chang Yulin,Wang Wei,Deng Wei,et al.Research of the Headway Distribution Models on Two-Lane Highways and Their Applications[J].Journal of Southeast University (Natural Science Edition),1999,29(1):108.[doi:10.3969/j.issn.1001-0505.1999.06.024]
[2]常玉林,王炜,曹洪.主车流服从 Erlang 分布下支路通行能力研究[J].东南大学学报(自然科学版),1998,28(3):98.[doi:10.3969/j.issn.1001-0505.1998.03.019]
 Chang Yulin,Wang Wei,Cao Hong,et al.Capacity of Inferior Lane at Unsignalized Intersection[J].Journal of Southeast University (Natural Science Edition),1998,28(1):98.[doi:10.3969/j.issn.1001-0505.1998.03.019]
[3]魏明,陈学武,孙博.一种车速截断对数正态分布的车队离散模型[J].东南大学学报(自然科学版),2013,43(4):885.[doi:10.3969/j.issn.1001-0505.2013.04.039]
 Wei Ming,Chen Xuewu,Sun Bo.Platoon dispersion model based on truncated lognormal distribution of speed[J].Journal of Southeast University (Natural Science Edition),2013,43(1):885.[doi:10.3969/j.issn.1001-0505.2013.04.039]
[4]王昊,刘振全,张志学,等.考虑双前导车的跟驰与换道联合模型[J].东南大学学报(自然科学版),2015,45(5):985.[doi:10.3969/j.issn.1001-0505.2015.05.029]
 Wang Hao,Liu Zhenquan,Zhang Zhixue,et al.Double-head car-following and lane-changing combined model[J].Journal of Southeast University (Natural Science Edition),2015,45(1):985.[doi:10.3969/j.issn.1001-0505.2015.05.029]

备注/Memo

备注/Memo:
作者简介:王建(1988—),男,硕士生;邓卫(联系人),男,博士,教授,博士生导师,dengwei@seu.edu.cn.
基金项目:“十一五”国家科技支撑计划资助项目(2006BAJ18B03).
引文格式: 王建,邓卫,赵金宝.基于改进型贝叶斯组合模型的短时交通流量预测[J].东南大学学报:自然科学版,2012,42(1):162-167.[doi:10.3969/j.issn.1001-0505.2012.01.030]
更新日期/Last Update: 2012-01-20