{"id":"doi:10.1016/j.inffus.2020.01.002","kind":"article","title":"Urban flow prediction from spatiotemporal data using machine learning: A survey","authors":["Peng Xie","Tianrui Li","Jia Liu","Shengdong Du","Xin Yang","Junbo Zhang"],"author_count":6,"year":2020,"published":"2020-01-10","venue":"Information Fusion","cited_by":301,"doi":"10.1016/j.inffus.2020.01.002","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.inffus.2020.01.002","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.inffus.2020.01.002","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W3000301417","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"retracted":false,"peer_reviewed":null,"categories":["Traffic Prediction and Management Techniques"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0).","topics":[{"slug":"ai-weather-climate","name":"AI Weather & Climate Modeling","domain_slug":"energy"}],"cited_in_dossiers":[]}