%0 Conference Paper %1 conf/icbdt/YeXP22 %A Ye, Rongkun %A Xu, Zhihao %A Pang, Junjie %B ICBDT %D 2022 %I ACM %K dblp %P 373-379 %T DDFM: A Novel Perspective on Urban Travel Demand Forecasting Based on the Ensemble Empirical Mode Decomposition and Deep Learning. %U http://dblp.uni-trier.de/db/conf/icbdt/icbdt2022.html#YeXP22 %@ 978-1-4503-9687-5

@inproceedings{conf/icbdt/YeXP22, added-at = {2022-12-25T00:00:00.000+0100}, author = {Ye, Rongkun and Xu, Zhihao and Pang, Junjie}, biburl = {https://www.bibsonomy.org/bibtex/2bde7a49509b0e6743cb865ef3681c160/dblp}, booktitle = {ICBDT}, crossref = {conf/icbdt/2022}, ee = {https://doi.org/10.1145/3565291.3565351}, interhash = {5d9b3a9651a7c9ade1d48ed1c7b56a75}, intrahash = {bde7a49509b0e6743cb865ef3681c160}, isbn = {978-1-4503-9687-5}, keywords = {dblp}, pages = {373-379}, publisher = {ACM}, timestamp = {2024-04-09T16:38:44.000+0200}, title = {DDFM: A Novel Perspective on Urban Travel Demand Forecasting Based on the Ensemble Empirical Mode Decomposition and Deep Learning.}, url = {http://dblp.uni-trier.de/db/conf/icbdt/icbdt2022.html#YeXP22}, year = 2022 }