{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:12:53Z","timestamp":1750219973162,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":16,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:00:00Z","timestamp":1666310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Shandong Provincial Natural Science Foundation, China","award":["ZR2022MF345"],"award-info":[{"award-number":["ZR2022MF345"]}]},{"name":"the Major Science and Technology Innovation Project of Shandong Province, China","award":["2020CXGC010110"],"award-info":[{"award-number":["2020CXGC010110"]}]},{"name":"Doctoral research start-up fund of Shandong Jiaotong University, China","award":["BS2021015"],"award-info":[{"award-number":["BS2021015"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,10,21]]},"DOI":"10.1145\/3569966.3569995","type":"proceedings-article","created":{"date-parts":[[2022,12,20]],"date-time":"2022-12-20T22:24:41Z","timestamp":1671575081000},"page":"93-96","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Metro Passenger Flow Prediction Based on Optimized BP Neural Network Algorithm"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8581-7607","authenticated-orcid":false,"given":"Fei","family":"Xu","sequence":"first","affiliation":[{"name":"Shandong Jiaotong University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1857-0461","authenticated-orcid":false,"given":"Song","family":"Gao","sequence":"additional","affiliation":[{"name":"Shandong Jiaotong University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,12,20]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tust.2021.103877"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.15302\/J-FEM-2017015"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2022.123612"},{"volume-title":"Short-term subway passenger flow prediction based on ARIMA[C]\/\/International Conference on Geo-Spatial Knowledge and Intelligence","year":"2017","key":"e_1_3_2_1_4_1","unstructured":"Yan D, Zhou J, Zhao Y , Short-term subway passenger flow prediction based on ARIMA[C]\/\/International Conference on Geo-Spatial Knowledge and Intelligence . Springer , Singapore , 2017 : 464-479. Yan D, Zhou J, Zhao Y, Short-term subway passenger flow prediction based on ARIMA[C]\/\/International Conference on Geo-Spatial Knowledge and Intelligence. Springer, Singapore, 2017: 464-479."},{"issue":"1","key":"e_1_3_2_1_5_1","first-page":"70","article-title":"Metro passenger flow forecast with a novel markov-grey model[J]","volume":"48","year":"2020","unstructured":"Wang Y, Ma J, Zhang J . Metro passenger flow forecast with a novel markov-grey model[J] . Periodica Polytechnica Transportation Engineering , 2020 , 48 ( 1 ): 70 - 75 . Wang Y, Ma J, Zhang J. Metro passenger flow forecast with a novel markov-grey model[J]. Periodica Polytechnica Transportation Engineering, 2020, 48(1): 70-75.","journal-title":"Periodica Polytechnica Transportation Engineering"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2907739"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2019.08.005"},{"key":"e_1_3_2_1_8_1","first-page":"1","article-title":"Research on forecast of rail traffic flow based on ARIMA model","volume":"1792","author":"Liu Shu Ying","unstructured":"Liu , Shu Ying , \" Research on forecast of rail traffic flow based on ARIMA model .\" Journal of Physics: Conference Series. Vol. 1792 . No. 1 . IOP Publishing, 2021. Liu, Shu Ying, \"Research on forecast of rail traffic flow based on ARIMA model.\" Journal of Physics: Conference Series. Vol. 1792. No. 1. IOP Publishing, 2021.","journal-title":"Journal of Physics: Conference Series."},{"key":"e_1_3_2_1_9_1","volume-title":"IOP Conference Series: Earth and Environmental Science.","volume":"632","author":"Li Zengxin","year":"2021","unstructured":"Li , Zengxin , \"Research on Prediction of Metro Surface Deformation Based on Ensemble Kalman Filter .\" IOP Conference Series: Earth and Environmental Science. Vol. 632 . No. 2. IOP Publishing , 2021 . Li, Zengxin, \"Research on Prediction of Metro Surface Deformation Based on Ensemble Kalman Filter.\" IOP Conference Series: Earth and Environmental Science. Vol. 632. No. 2. IOP Publishing, 2021."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3072743"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2973406"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106960"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-016-2474-6"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.52.2318"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2019.03782"},{"key":"e_1_3_2_1_16_1","unstructured":"Song Yue-Gang Yu-Long Zhou and Ren-Jie Han. \"Neural networks for stock price prediction.\" arXiv preprint arXiv:1805.11317 (2018).  Song Yue-Gang Yu-Long Zhou and Ren-Jie Han. \"Neural networks for stock price prediction.\" arXiv preprint arXiv:1805.11317 (2018)."}],"event":{"name":"CSSE 2022: 2022 5th International Conference on Computer Science and Software Engineering","acronym":"CSSE 2022","location":"Guilin China"},"container-title":["Proceedings of the 5th International Conference on Computer Science and Software Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3569966.3569995","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3569966.3569995","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:19Z","timestamp":1750182559000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3569966.3569995"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,21]]},"references-count":16,"alternative-id":["10.1145\/3569966.3569995","10.1145\/3569966"],"URL":"https:\/\/doi.org\/10.1145\/3569966.3569995","relation":{},"subject":[],"published":{"date-parts":[[2022,10,21]]},"assertion":[{"value":"2022-12-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}