SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Exploring Imputation Techniques for Missing Data in Transportation Management Systems
0 references·8 citing·21 second hop
Exploring Imputation Techniques for Missing Data in Transportation Management Systems (2003)Exploring Imputation Techniques for Missi…Matrix and Tensor Based Methods for Missing Data Estimation in Large Traffic Networks (2016)Matrix and Tensor Based Metho…Data-Driven Imputation Method for Traffic Data in Sectional Units of Road Links (2016)Data-Driven Imputation Method…An efficient realization of deep learning for traffic data imputation (2016)An efficient realization of d…Tensor based missing traffic data completion with spatial–temporal correlation (2015)Tensor based missing traffic …Traffic Flow Prediction for Road Transportation Networks With Limited Traffic Data (2014)Traffic Flow Prediction for R…Efficient missing data imputing for traffic flow by considering temporal and spatial dependence (2013)Efficient missing data imputi…A tensor-based method for missing traffic data completion (2013)A tensor-based method for mis…PPCA-Based Missing Data Imputation for Traffic Flow Volume: A Systematical Approach (2009)PPCA-Based Missing Data Imput…Problems in Measuring Change (1965)Modeling and Forecasting Vehicular Traffic Flow as a Seasonal ARIMA Process: Theoretical Basis and Empirical Results (2003)Statistical methods versus neural networks in transportation research: Differences, similarities and some insights (2010)A Bayesian tensor decomposition approach for spatiotemporal traffic data imputation (2018)Fitting autoregressive models for prediction (1969)Modelling Transport (2011)Survey on traffic prediction in smart cities (2018)Deep Irregular Convolutional Residual LSTM for Urban Traffic Passenger Flows Prediction (2019)Flow Prediction in Spatio-Temporal Networks Based on Multitask Deep Learning (2019)Combining kohonen maps with arima time series models to forecast traffic flow (1996)A Bayesian Network Approach to Traffic Flow Forecasting (2006)Archived Intelligent Transportation System Data Quality: Preliminary Analyses of San Antonio TransGuide Data (2000)A novel wavelet-SVM short-time passenger flow prediction in Beijing subway system (2015)Performance measurement system (2002)Estimation of missing traffic counts using factor, genetic, neural, and regression techniques (2004)Missing traffic data: comparison of imputation methods (2013)The retrieval of intra-day trend and its influence on traffic prediction (2012)Accurate freeway travel time prediction with state-space neural networks under missing data (2005)Traffic Flow Prediction With Big Data: A Deep Learning Approach (2014)A novel passenger flow prediction model using deep learning methods (2017)The station-free sharing bike demand forecasting with a deep learning approach and large-scale datasets (2018)
this work references cited by second hop

References

No references inside the corpus for this window.

Cited by

  • 2009PPCA-Based Missing Data Imputation for Traffic Flow Volume: A Systematical Approach445 cited
  • 2013A tensor-based method for missing traffic data completion441 cited
  • 2014Traffic Flow Prediction for Road Transportation Networks With Limited Traffic Data346 cited
  • 2016An efficient realization of deep learning for traffic data imputation320 cited
  • 2013Efficient missing data imputing for traffic flow by considering temporal and spatial dependence304 cited
  • 2016Data-Driven Imputation Method for Traffic Data in Sectional Units of Road Links161 cited
  • 2016Matrix and Tensor Based Methods for Missing Data Estimation in Large Traffic Networks160 cited
  • 2015Tensor based missing traffic data completion with spatial–temporal correlation154 cited

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