SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Exploiting dynamic spatio-temporal graph convolutional neural networks for citywide traffic flows prediction
13 references·0 citing·30 second hop
Exploiting dynamic spatio-temporal graph convolutional neural networks for citywide traffic flows prediction (2021)Exploiting dynamic spatio-temporal graph …Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting (2018)Spatio-Temporal Graph Convolu…Predicting citywide crowd flows using deep spatio-temporal residual networks (2018)Predicting citywide crowd flo…Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction (2017)Learning Traffic as Images: A…Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting (2017)Diffusion Convolutional Recur…Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction (2017)Deep Spatio-Temporal Residual…DNN-based prediction model for spatio-temporal data (2016)DNN-based prediction model fo…Traffic Flow Prediction With Big Data: A Deep Learning Approach (2014)Traffic Flow Prediction With …Short-Term Traffic Flow Forecasting: An Experimental Comparison of Time-Series Analysis and Supervised Learning (2013)Short-Term Traffic Flow Forec…Predicting Taxi–Passenger Demand Using Streaming Data (2013)Predicting Taxi–Passenger Dem…Vector Autoregressive Models for Multivariate Time Series (2007)Vector Autoregressive Models …A Bayesian Network Approach to Traffic Flow Forecasting (2006)A Bayesian Network Approach t…Vector Autoregressive Models for Multivariate Time Series (2003)Vector Autoregressive Models …Modeling and Forecasting Vehicular Traffic Flow as a Seasonal ARIMA Process: Theoretical Basis and Empirical Results (2003)Modeling and Forecasting Vehi…Dynamic prediction of traffic volume through Kalman filtering theory (1984)Exponential smoothing: The state of the art (1985)Introduction to Time Series and Forecasting (2002)Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (2019)T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction (2019)Forecasting with artificial neural networks: (1998)Travel-Time Prediction With Support Vector Regression (2004)A hybrid deep learning based traffic flow prediction method and its understanding (2018)Traffic Flow Prediction via Spatial Temporal Graph Neural Network (2020)Deep Learning on Traffic Prediction: Methods, Analysis, and Future Directions (2022)Time series forecasting using a hybrid ARIMA and neural network model (2003)Automatic Time Series Forecasting: The forecast Package for R (2008)Understanding individual human mobility patterns (2008)Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach (2017)Ridesourcing systems: A framework and review (2019)Data-intensive applications, challenges, techniques and technologies: A survey on Big Data (2014)LSTM network: a deep learning approach for short‐term traffic forecast (2017)Combining kohonen maps with arima time series models to forecast traffic flow (1996)Traffic Flow Forecasting: Comparison of Modeling Approaches (1997)PPCA-Based Missing Data Imputation for Traffic Flow Volume: A Systematical Approach (2009)DeepPF: A deep learning based architecture for metro passenger flow prediction (2019)Prediction of human emergency behavior and their mobility following large-scale disaster (2014)Methodologies for Cross-Domain Data Fusion: An Overview (2015)Traffic prediction in a bike-sharing system (2015)GMAN: A Graph Multi-Attention Network for Traffic Prediction (2020)Long short-term memory neural network for traffic speed prediction using remote microwave sensor data (2015)Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction (2018)Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting (2019)Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks (2017)Graph WaveNet for Deep Spatial-Temporal Graph Modeling (2019)
this work references cited by second hop

References

  • 2018Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting6,048 cited
  • 2017Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting3,639 cited
  • 2014Traffic Flow Prediction With Big Data: A Deep Learning Approach3,073 cited
  • 2017Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction2,450 cited
  • 2003Modeling and Forecasting Vehicular Traffic Flow as a Seasonal ARIMA Process: Theoretical Basis and Empirical Results2,210 cited
  • 2017Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction1,442 cited
  • 2006A Bayesian Network Approach to Traffic Flow Forecasting803 cited
  • 2013Short-Term Traffic Flow Forecasting: An Experimental Comparison of Time-Series Analysis and Supervised Learning763 cited
  • 2013Predicting Taxi–Passenger Demand Using Streaming Data739 cited
  • 2016DNN-based prediction model for spatio-temporal data739 cited
  • 2018Predicting citywide crowd flows using deep spatio-temporal residual networks534 cited
  • 2003Vector Autoregressive Models for Multivariate Time Series361 cited
  • 2007Vector Autoregressive Models for Multivariate Time Series179 cited

Cited by

No citing works inside the corpus for this window.

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work