Exploring the role of wavelet decomposition order in deep learning-based network-wide traffic predictionOA
Exploring the role of wavelet decomposition order in deep learning-based network-wide traffic prediction
Mohammad Javad Hassanzada;Iuliia Yamnenko;Constantinos Antoniou
Department of Mobility Systems Engineering,Technical University of Munich,Munich 80333,GermanyDepartment of Mobility Systems Engineering,Technical University of Munich,Munich 80333,Germany||Department of Electronic Devices and Systems,National Technical University of Ukraine"Igor Sikorsky Kyiv Polytechnic Institute",Kyiv 03056,UkraineDepartment of Mobility Systems Engineering,Technical University of Munich,Munich 80333,Germany
Network traffic forecastDeep neural networkWavelet processing orderMLPHaar waveletSARIMA
Network traffic forecastDeep neural networkWavelet processing orderMLPHaar waveletSARIMA
《交通运输工程学报（英文版）》 2026 (1)
148-167,20
This research was funded by the Institute for Advanced Study at Technical University of Munich(TUM-IAS)and the Philipp Schwartz Initiative offered by the Alexander von Humboldt Foundation,Germany.
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