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A spatiotemporal correlative k-nearest neighbor model for short-term traffic multistep forecasting
11 references·11 citing·36 second hop
A spatiotemporal correlative k-nearest neighbor model for short-term traffic multistep forecasting (2015)A spatiotemporal correlative k-nearest ne…Long short-term memory neural network for traffic speed prediction using remote microwave sensor data (2015)Long short-term memory neural…Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory (2015)Large-Scale Transportation Ne…Short-term traffic volume forecasting: A k-nearest neighbor approach enhanced by constrained linearly sewing principle component algorithm (2014)Short-term traffic volume for…Short-term traffic forecasting: Where we are and where we’re going (2014)Short-term traffic forecastin…New Bayesian combination method for short-term traffic flow forecasting (2014)New Bayesian combination meth…Adaptive Kalman filter approach for stochastic short-term traffic flow rate prediction and uncertainty quantification (2014)Adaptive Kalman filter approa…A travel time reliability model of urban expressways with varying levels of service (2014)A travel time reliability mod…Real-time road traffic prediction with spatio-temporal correlations (2010)Real-time road traffic predic…Modeling and Forecasting Vehicular Traffic Flow as a Seasonal ARIMA Process: Theoretical Basis and Empirical Results (2003)Modeling and Forecasting Vehi…Comparison of parametric and nonparametric models for traffic flow forecasting (2002)Comparison of parametric and …Application of Subset Autoregressive Integrated Moving Average Model for Short-Term Freeway Traffic Volume Forecasting (1999)Application of Subset Autoreg…Using support vector regression and K-nearest neighbors for short-term traffic flow prediction based on maximal information coefficient (2022)Using support vector regressi…Traffic prediction using artificial intelligence: Review of recent advances and emerging opportunities (2022)Traffic prediction using arti…Learning Dynamic and Hierarchical Traffic Spatiotemporal Features With Transformer (2021)Learning Dynamic and Hierarch…Optimized Graph Convolution Recurrent Neural Network for Traffic Prediction (2020)Optimized Graph Convolution R…Machine Learning-based traffic prediction models for Intelligent Transportation Systems (2020)Machine Learning-based traffi…A Survey on Modern Deep Neural Network for Traffic Prediction: Trends, Methods and Challenges (2020)A Survey on Modern Deep Neura…A graph CNN-LSTM neural network for short and long-term traffic forecasting based on trajectory data (2020)A graph CNN-LSTM neural netwo…Spatiotemporal Traffic Flow Prediction with KNN and LSTM (2019)Spatiotemporal Traffic Flow P…Multistep speed prediction on traffic networks: A deep learning approach considering spatio-temporal dependencies (2019)Multistep speed prediction on…Survey on traffic prediction in smart cities (2018)Survey on traffic prediction …Road Traffic Forecasting: Recent Advances and New Challenges (2018)Road Traffic Forecasting: Rec…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)Aggregation of space-time processes (2003)Optimized and meta-optimized neural networks for short-term traffic flow prediction: A genetic approach (2005)Predicting Taxi–Passenger Demand Using Streaming Data (2013)A hybrid deep learning based traffic flow prediction method and its understanding (2018)Combining forecasts: A review and annotated bibliography (1989)Combining forecasts: A review and annotated bibliography (1990)Statistical and Econometric Methods for Transportation Data Analysis (2003)Deep learning for short-term traffic flow prediction (2017)Time Series Analysis: Forecasting and Control. (1978)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach (2017)Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks (2017)Understanding Road Usage Patterns in Urban Areas (2012)Deep Architecture for Traffic Flow Prediction: Deep Belief Networks With Multitask Learning (2014)An Improved Fuzzy Neural Network for Traffic Speed Prediction Considering Periodic Characteristic (2017)Spatio-Temporal Meta-Graph Learning for Traffic Forecasting (2023)Book Review: Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control (1977)A multivariate state space approach for urban traffic flow modeling and prediction (2003)Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks (2011)A Hybrid Deep Learning Model With Attention-Based Conv-LSTM Networks for Short-Term Traffic Flow Prediction (2020)Traffic Flow Prediction With Big Data: A Deep Learning Approach (2014)Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting (2018)T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction (2019)Deep Learning Architecture for Short-Term Passenger Flow Forecasting in Urban Rail Transit (2020)A Review of Traffic Congestion Prediction Using Artificial Intelligence (2021)Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting (2017)A Survey of Traffic Prediction: from Spatio-Temporal Data to Intelligent Transportation (2021)Using LSTM and GRU neural network methods for traffic flow prediction (2016)LSTM network: a deep learning approach for short‐term traffic forecast (2017)GMAN: A Graph Multi-Attention Network for Traffic Prediction (2020)
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References

  • 2015Long short-term memory neural network for traffic speed prediction using remote microwave sensor data2,259 cited
  • 2003Modeling and Forecasting Vehicular Traffic Flow as a Seasonal ARIMA Process: Theoretical Basis and Empirical Results2,210 cited
  • 2014Short-term traffic forecasting: Where we are and where we’re going1,248 cited
  • 2002Comparison of parametric and nonparametric models for traffic flow forecasting1,016 cited
  • 2010Real-time road traffic prediction with spatio-temporal correlations674 cited
  • 2014Adaptive Kalman filter approach for stochastic short-term traffic flow rate prediction and uncertainty quantification653 cited
  • 1999Application of Subset Autoregressive Integrated Moving Average Model for Short-Term Freeway Traffic Volume Forecasting546 cited
  • 2015Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory508 cited
  • 2014Short-term traffic volume forecasting: A k-nearest neighbor approach enhanced by constrained linearly sewing principle component algorithm189 cited
  • 2014New Bayesian combination method for short-term traffic flow forecasting187 cited
  • 2014A travel time reliability model of urban expressways with varying levels of service42 cited

Cited by

  • 2020A Survey on Modern Deep Neural Network for Traffic Prediction: Trends, Methods and Challenges424 cited
  • 2020A graph CNN-LSTM neural network for short and long-term traffic forecasting based on trajectory data

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389 cited
  • 2018Road Traffic Forecasting: Recent Advances and New Challenges387 cited
  • 2020Optimized Graph Convolution Recurrent Neural Network for Traffic Prediction384 cited
  • 2020Machine Learning-based traffic prediction models for Intelligent Transportation Systems350 cited
  • 2018Survey on traffic prediction in smart cities331 cited
  • 2022Traffic prediction using artificial intelligence: Review of recent advances and emerging opportunities305 cited
  • 2021Learning Dynamic and Hierarchical Traffic Spatiotemporal Features With Transformer302 cited
  • 2019Spatiotemporal Traffic Flow Prediction with KNN and LSTM300 cited
  • 2019Multistep speed prediction on traffic networks: A deep learning approach considering spatio-temporal dependencies297 cited
  • 2022Using support vector regression and K-nearest neighbors for short-term traffic flow prediction based on maximal information coefficient296 cited