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If you want to properly guide the local passenger flow and make a reasonable deployment of operating buses, it is necessary to grasp the changing law of public transportation short-term passenger flow. This paper builds a short-term passenger flow prediction model for urban public transportation based on the idea of integrated learning. The goal is to use the integrated model to accurately predict the short-term passenger flow of urban public transportation, using Multivariable Linear Regression (MLR), K-Nearest Neighbor (KNN), eXtreme Gradient Boosting (XGBoost), and Gated Recurrent Unit (GRU) as the four seed models, and then use regression algorithm to integrate the model and predict the passenger flow, station boarding and landing, and cross-sectional passenger flow data of the typical representative line 428 in the \u201cHuitian Area\u201d of Beijing from January 1, 2020, to May 31, 2020. Finally, the prediction results of the submodels are compared with those of the integrated model to verify the superiority of the integrated model. The research results of this paper can enrich the short-term passenger flow forecasting system of urban public transportation and provide effective data support and scientific basis for the passenger flow, vehicle management, and dispatch of urban public transportation.<\/jats:p>","DOI":"10.1155\/2020\/6694186","type":"journal-article","created":{"date-parts":[[2020,12,19]],"date-time":"2020-12-19T18:50:05Z","timestamp":1608403805000},"page":"1-13","source":"Crossref","is-referenced-by-count":10,"title":["An Ensemble Learning Model for Short-Term Passenger Flow Prediction"],"prefix":"10.1155","volume":"2020","author":[{"given":"Xiangping","family":"Wang","sequence":"first","affiliation":[{"name":"School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haifeng","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baoyu","family":"Li","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6761-2288","authenticated-orcid":true,"given":"Ziyang","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6811-5045","authenticated-orcid":true,"given":"Jing","family":"Li","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2011.06.009"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.3141\/1644-14"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.3141\/1678-22"},{"issue":"2","key":"4","first-page":"135","article-title":"Passenger flow prediction of inbound and outbound stations of urban rail transit based on product ARIMA model","volume":"38","author":"C. 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