Deep Learning Architecture for Short-Term Passenger Flow Forecasting in Urban Rail Transit
暂无分享,去创建一个
Zhiyong Cui | Feng Chen | Yadi Zhu | Jinlei Zhang | Yinan Guo | Zhiyong Cui | Jinlei Zhang | Feng Chen | Yadi Zhu | Yinan Guo
[1] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[2] Ning Zhang,et al. Short-term forecasting of urban rail transit ridership based on ARIMA and wavelet decomposition , 2018 .
[3] Tsuyoshi Murata,et al. {m , 1934, ACML.
[4] Peter C. Y. Chen,et al. LSTM network: a deep learning approach for short-term traffic forecast , 2017 .
[5] Sattar Hashemi,et al. Road Traffic Prediction Using Context-Aware Random Forest Based on Volatility Nature of Traffic Flows , 2013, ACIIDS.
[6] Enrique Onieva,et al. A graph CNN-LSTM neural network for short and long-term traffic forecasting based on trajectory data , 2020 .
[7] Bin Ran,et al. Short-to-medium Term Passenger Flow Forecasting for Metro Stations using a Hybrid Model , 2017, KSCE Journal of Civil Engineering.
[8] Yunpeng Wang,et al. Long short-term memory neural network for traffic speed prediction using remote microwave sensor data , 2015 .
[9] Yinhai Wang,et al. Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting , 2018, IEEE Transactions on Intelligent Transportation Systems.
[10] Xiao-Ming Wu,et al. Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning , 2018, AAAI.
[11] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[12] Billy M. Williams,et al. Adaptive Seasonal Time Series Models for Forecasting Short-Term Traffic Flow , 2007 .
[13] Philip S. Yu,et al. A Comprehensive Survey on Graph Neural Networks , 2019, IEEE Transactions on Neural Networks and Learning Systems.
[14] Jing Li,et al. Graph CNNs for Urban Traffic Passenger Flows Prediction , 2018, 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI).
[15] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[16] Stéphane Bonnevay,et al. Dynamic Bayesian networks with Gaussian mixture models for short-term passenger flow forecasting , 2017, 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE).
[17] Qingchao Liu,et al. Short‐Term Traffic Speed Forecasting Based on Attention Convolutional Neural Network for Arterials , 2018, Comput. Aided Civ. Infrastructure Eng..
[18] Byeonghyeop Yu,et al. Forecasting road traffic speeds by considering area-wide spatio-temporal dependencies based on a graph convolutional neural network (GCN) , 2020 .
[19] Ning Zhang,et al. Forecasting of Short-Term Metro Ridership with Support Vector Machine Online Model , 2018, Journal of Advanced Transportation.
[20] Yu Liu,et al. T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction , 2018, IEEE Transactions on Intelligent Transportation Systems.
[21] Eleni I. Vlahogianni,et al. Short‐term traffic forecasting: Overview of objectives and methods , 2004 .
[22] Billy M. Williams,et al. Modeling and Forecasting Vehicular Traffic Flow as a Seasonal ARIMA Process: Theoretical Basis and Empirical Results , 2003, Journal of Transportation Engineering.
[23] Bin Ran,et al. Day-ahead traffic flow forecasting based on a deep belief network optimized by the multi-objective particle swarm algorithm , 2019, Knowl. Based Syst..
[24] Mohamed Abdel-Aty,et al. Predicting Freeway Crashes from Loop Detector Data by Matched Case-Control Logistic Regression , 2004 .
[25] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[26] Yang Liu,et al. DeepPF: A deep learning based architecture for metro passenger flow prediction , 2019, Transportation Research Part C: Emerging Technologies.
[27] Li Li,et al. Using LSTM and GRU neural network methods for traffic flow prediction , 2016, 2016 31st Youth Academic Annual Conference of Chinese Association of Automation (YAC).
[28] Shu Yu,et al. Hybrid GA Based Online Support Vector Machine Model for Short-Term Traffic Flow Forecasting , 2007, APPT.
[29] Timothy Baldwin,et al. Semi-supervised User Geolocation via Graph Convolutional Networks , 2018, ACL.
[30] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[31] Jian Sun,et al. Identity Mappings in Deep Residual Networks , 2016, ECCV.
[32] Bin Ran,et al. A hybrid deep learning based traffic flow prediction method and its understanding , 2018 .
[33] Wang Peng,et al. Network Traffic Prediction Based on Improved BP Wavelet Neural Network , 2008, 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing.
[34] Yong Wang,et al. Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction , 2017, Sensors.
[35] Henry X. Liu,et al. Use of Local Linear Regression Model for Short-Term Traffic Forecasting , 2003 .
[36] Yu Zheng,et al. Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction , 2016, AAAI.
[37] Fei-Yue Wang,et al. Traffic Flow Prediction With Big Data: A Deep Learning Approach , 2015, IEEE Transactions on Intelligent Transportation Systems.
[38] Haiying Li,et al. Short-term passenger flow prediction under passenger flow control using a dynamic radial basis function network , 2019, Appl. Soft Comput..
[39] Yang Li,et al. Forecasting short-term subway passenger flow under special events scenarios using multiscale radial basis function networks ☆ , 2017 .
[40] Yang Ying,et al. ST-LSTM: A Deep Learning Approach Combined Spatio-Temporal Features for Short-Term Forecast in Rail Transit , 2019, Journal of Advanced Transportation.
[41] Danna Zhou,et al. d. , 1934, Microbial pathogenesis.
[42] Svetha Venkatesh,et al. Column Networks for Collective Classification , 2016, AAAI.
[43] Dehui Kong,et al. Improved Spatio-Temporal Residual Networks for Bus Traffic Flow Prediction , 2019, Applied Sciences.
[44] Zhen Xie,et al. Short-Term Abnormal Passenger Flow Prediction Based on the Fusion of SVR and LSTM , 2019, IEEE Access.
[45] Xianfeng Tang,et al. Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction , 2018, AAAI.
[46] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[47] Bin Ran,et al. Online Recursive Algorithm for Short-Term Traffic Prediction , 2004 .
[48] Bin Ran,et al. Missing Value Imputation for Traffic-Related Time Series Data Based on a Multi-View Learning Method , 2019, IEEE Transactions on Intelligent Transportation Systems.
[49] Yuan Liu,et al. Short-term forecasting of rail transit passenger flow based on long short-term memory neural network , 2018, 2018 International Conference on Intelligent Rail Transportation (ICIRT).
[50] Yanyan Xu,et al. Short-term traffic volume prediction using classification and regression trees , 2013, 2013 IEEE Intelligent Vehicles Symposium (IV).
[51] Michael J Demetsky,et al. TRAFFIC FLOW FORECASTING: COMPARISON OF MODELING APPROACHES , 1997 .
[52] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[53] Yinhai Wang,et al. Multistep speed prediction on traffic networks: A deep learning approach considering spatio-temporal dependencies , 2019, Transportation Research Part C: Emerging Technologies.
[54] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[55] Yi Zhang,et al. Short-term traffic flow forecasting of urban network based on dynamic STARIMA model , 2009, 2009 12th International IEEE Conference on Intelligent Transportation Systems.
[56] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[57] Bernard Ghanem,et al. DeepGCNs: Can GCNs Go As Deep As CNNs? , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[58] I Okutani,et al. Dynamic prediction of traffic volume through Kalman Filtering , 1984 .
[59] Yao Xiang-min. Dynamic origin-destination matrix estimation for urban rail transit based on averaging strategy , 2016 .
[60] Sa-Kwang Song,et al. DeepTC: ConvLSTM Network for Trajectory Prediction of Tropical Cyclone using Spatiotemporal Atmospheric Simulation Data , 2018 .
[61] Peng Gao,et al. Predicting Station-Level Short-Term Passenger Flow in a Citywide Metro Network Using Spatiotemporal Graph Convolutional Neural Networks , 2019, ISPRS Int. J. Geo Inf..
[62] Gary A. Davis,et al. Nonparametric Regression and Short‐Term Freeway Traffic Forecasting , 1991 .
[63] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.