
重庆交通大学学报(自然科学版) ›› 2021, Vol. 40 ›› Issue (11): 60-66.DOI: 10.3969/j.issn.1674-0696.2021.11.09
赵顗,沈玲宏,马健霄,邱烜利
收稿日期:2020-06-09
修回日期:2020-10-12
发布日期:2021-11-24
作者简介:赵顗(1989—),男,安徽池州人,讲师,博士,主要从事交通运输规划与管理方面的研究。E-mail:zhaoyi207@126.com
通信作者:沈玲宏(1995—),女,江苏丹阳人,硕士研究生,主要从事交通运输规划与管理方面的研究。E-mail:1547193251@qq.com
基金资助:ZHAO Yi, SHEN Linghong, MA Jianxiao, QIU Xuanli
Received:2020-06-09
Revised:2020-10-12
Published:2021-11-24
摘要: 针对交通小区生成交通的短时预测需求,提出了综合小波分析和BP神经网络的短时预测方法。预测方法主要利用dbN小波函数对交通小区生成交通进行小波分解,利用BP神经网络对分解后的多频段波形进行短时预测,最后通过波形重构获得交通小区生成交通的短时预测结果。在构建综合小波分析和BP神经网络短时预测模型基础上,采集交通小区的实际交通生成数据,并构建短时预测的对比模型,检验构建模型的预测精度。检验结果表明:在交通小区的生成交通短时预测方面,综合小波分析和BP神经网络的组合预测模型比单独采用BP神经网络进行预测的精度更高。
中图分类号:
赵顗,沈玲宏,马健霄,邱烜利. 综合小波分解和BP神经网络的交通小区生成交通短时预测[J]. 重庆交通大学学报(自然科学版), 2021, 40(11): 60-66.
ZHAO Yi, SHEN Linghong, MA Jianxiao, QIU Xuanli. Traffic Short-Term Prediction Generated by Wavelet Decomposition and BP Neural Network of Traffic Zone[J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(11): 60-66.
| [1] 赵顗.面向城市道路网交通瓶颈预警的信号控制关键技术研究[D].南京:东南大学,2018.
Zhao Yi.Research on Key Technologies of Signal Control for Traffic Bottleneck Early Warning of Urban Road Network[D]. Nanjing: Southeast University, 2018. [2] ZHANG Yanru, ZHANG Yunlong. A comparative study of three multi-variate short-term freeway traffic flow forecasting methods with missing data[J]. Journal of Intelligent Transportation Systems, 2016, 20(3): 205-218. [3] WEI Chien-Hung, LEE Ying. Development of freeway travel time for-ecasting models by integrating different sources of traffic data[J]. IEEE Transactions on Vehicular Technology, 2007, 56(6): 3682-3694. [4] YU Runze, LAO Yunteng, MA Xiaolei, et al. Short-term traffic flow forecasting for freeway incident-induced delay estimation[J]. Journal of Intelligent Transportation Systems, 2014, 18(3): 254-263. [5] ZOU Yajie, HUA Xuedong, ZHANG Yanru, et al. Hybrid short-term freeway speed prediction methods based on periodic analysis[J]. Canadian Journal of Civil Engineering, 2015, 42(8): 570-582. [6] CHANG Ganglen, SU Chih-Chiang. Predicting intersection queue with neural network models[J]. Transportation Research Part C: Emerging Technologies, 1995, 3(3): 175-191. [7] LYONS G, MCDONALD M, HOUNSELL N, et al. Urban traffic mana-gement; the viability of short term congestion forecasting using artificial neural networks[C]∥24th European Transport Forum, Traffic Management and Road Safety. Brunel University, England, 1996: 1-13. [8] YIN Hongbin, WONG S C, XU Jianmin, et al. Urban traffic flow predic-tion using a fuzzy-neural approach[J]. Transportation Research Part C: Emerging Technologies, 2002, 10(2): 85-98. [9] STATHOPOULOS A, KARLAFTIS M G. A multivariate state space app-roach for urban traffic flow modeling and prediction[J].Transportation Research Part C: Emerging Technologies, 2003, 11(2): 121-135. [10] 赵鹏,李璐.基于ARIMA模型的城市轨道交通进站量预测研究[J].重庆交通大学学报(自然科学版),2020,39(1):40-44. ZHAO Peng, LI Lu. Prediction of urban rail transit station inflows based on ARIMA model[J].Journal of Chongqing Jiaotong University (Natural Science), 2020, 39(1): 40-44. [11] SMITH B L, DEMETSKY M J. Traffic flow forecasting: Comparison of modeling approaches[J].Journal of Transportation Engineering, 1997, 123 (4): 261-266. [12] 贺国光,马寿峰,李宇.基于小波分解与重构的交通流短时预测法[J].系统工程理论与实践,2002,22(9):101-106. HE Guoguang, MA Shoufeng, LI Yu. Study on the short-term forecasting for traffic flow based on wavelet analysis[J]. System Engineering—Theory and Practice, 2002, 22(9): 101-106. [13] 彭勇,沙晓宇,刘世洁,等.基于PFV策略的连续型元胞自动机交通流模型[J].交通运输系统工程与信息,2019,19(3):75-80. PENG Yong, SHA Xiaoyu, LIU Shijie, et al. Continuous cellular automata traffic flow model based on PFV strategy[J]. Journal of Transportation System Engineering and Information Technology, 2019, 19(3): 75-80. [14] SMITH B L, DEMETSKY M J. Short-term traffic flow prediction: Neural network approach[J].Journal of the Transportation Research Board, 1994, 1453: 98-104. [15] 殷礼胜,唐圣期,李胜,等.基于整合移动平均自回归和遗传粒子群优化小波神经网络组合模型的交通流预测[J].电子与信息学报,2019,41(9):2273- 2279. YIN Lisheng, TANG Shengqi, LI Sheng, et al. Traffic flow predic-tion based on hybrid model of auto-regressive integrated moving average and genetic particle swarm optimization wavelet neural network[J]. Journal of Electronics and Information Technology, 2019, 41(9): 2273-2279. [16] YANG Wen, YANG Dongyuan, ZHAO Yali, et al. Traffic flow predic-tion based on wavelet transform and radial basis function network[C]∥ 2000 International Conference on Logistics Systems & Intelligent Management. U.S.A.: IEEE, 2010. [17] WEI Yongtao, WANG Jinkuan, WANG Cuirong, et al. Network traffic prediction by traffic decomposition[C]∥ 2012 5th International Conference on Intelligent Networks & Intelligent Systems. U.S.A.: IEEE, 2012. [18] 翁小雄,汪周盼.基于BP神经网络的轨道交通客流分布模型[J].重庆交通大学学报(自然科学版),2018,37(1):104-108. WENG Xiaoxiong, WANG Zhoupan. Passenger flow distribution model for urban rail transit based on BP neural networks[J]. Journal of Chongqing Jiaotong University(Natural Science), 2018, 37(1): 104-108. [19] 刘静,李亮,关伟,等.基于神经网络的北京环路交通流短期预测研究[J].交通运输系统工程与信息,2005,5(6):110-115. LIU Jing, LI Liang, GUAN Wei, et al. Short-term prediction of traffic flow in Beijing ring road based on neural network[J]. Journal of Transportation Systems Engineering and Information Technology, 2005, 5(6): 110-115. [20] LIU Zhongbo, YANG Zhaosheng, GAO Peng. Research on the short-term traffic flow prediction method based on BP neural networks[C]∥ World Automation Congress(WAC), 2012. U.S.A.: IEEE, 2012. |
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