2009 · 10 citations · 2 references
EngineeringCivil EngineeringComputer ScienceMachine LearningPredictive AnalyticsTransportation EngineeringIntelligent Transportation SystemsTime Series ForecastingTraffic EngineeringTraffic Flow AnalysisTraffic Flow ManagementTraffic Flow TheoryEmpirical Mode DecompositionMachine Learning For Traffic AnalysisPredictionShort-term Traffic PredictionTraffic Flow ForecastingTraffic Flow ModelingTraffic Flow PredictionTraffic Prediction
An approach to short-term traffic flow prediction based on empirical mode decomposition (EMD) and artificial neural network (ANN) is proposed. The traffic flow is decomposed into different modes by EMD, and these different modes are predicted by appropriate ANNs. The predictive traffic flow is obtained by adding up all predictive values. This method is used to predict traffic flow with the actual measurement data. The results show that the proposed method has high predictive accuracy, and is more successful than the outcome of directly using ANN prediction.
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Norden E. Huang, Steven Long, Man‐Li C. Wu et al. · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 1998 · 23.3K citations · Full text
Computing, Computational Engineering, Biomedical Signal Processing +16