Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks
Top Cited Papers
- 30 April 2012
- journal article
- Published by Elsevier BV in Transportation Research Part C: Emerging Technologies
- Vol. 21 (1), 148-162
- https://doi.org/10.1016/j.trc.2011.06.009
Abstract
No abstract availableKeywords
This publication has 60 references indexed in Scilit:
- Exploring time variants for short-term passenger flowJournal of Transport Geography, 2011
- Seasonal ARIMA forecasting of inbound air travel arrivals to TaiwanTransportmetrica, 2009
- Design of experiments on neural network's training for nonlinear time series forecastingNeurocomputing, 2009
- Empirical mode decomposition: a method for analyzing neural dataNeurocomputing, 2005
- A study of the characteristics of white noise using the empirical mode decomposition methodProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2004
- A confidence limit for the empirical mode decomposition and Hilbert spectral analysisProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2003
- Time series forecasting using a hybrid ARIMA and neural network modelNeurocomputing, 2003
- Time series forecasts of international travel demand for AustraliaTourism Management, 2002
- Forecasting with artificial neural networks:: The state of the artInternational Journal of Forecasting, 1998
- Wrappers for feature subset selectionArtificial Intelligence, 1997