{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T16:46:51Z","timestamp":1784566011461,"version":"3.55.0"},"reference-count":34,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,10,19]],"date-time":"2021-10-19T00:00:00Z","timestamp":1634601600000},"content-version":"vor","delay-in-days":291,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["LY20F020013"],"award-info":[{"award-number":["LY20F020013"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003467","name":"Hangzhou Dianzi University","doi-asserted-by":"publisher","award":["JXGG2020YB009"],"award-info":[{"award-number":["JXGG2020YB009"]}],"id":[{"id":"10.13039\/501100003467","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003467","name":"Hangzhou Dianzi University","doi-asserted-by":"publisher","award":["JXALK2020001"],"award-info":[{"award-number":["JXALK2020001"]}],"id":[{"id":"10.13039\/501100003467","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>Accurate monitoring of air quality can no longer meet people\u2019s needs. People hope to predict air quality in advance and make timely warnings and defenses to minimize the threat to life. This paper proposed a new air quality spatiotemporal prediction model to predict future air quality and is based on a large number of environmental data and a long short\u2010term memory (LSTM) neural network. In order to capture the spatial and temporal characteristics of the pollutant concentration data, the data of the five sites with the highest correlation of time\u2010series concentration of PM2.5 (particles with aerodynamic diameter \u22642.5\u2009mm) at the experimental site were first extracted, and the weather data and other pollutant data at the same time were merged in the next step, extracting advanced spatiotemporal features through long\u2010 and short\u2010term memory neural networks. The model presented in this paper was compared with other baseline models on the hourly PM2.5 concentration data set collected at 35 air quality monitoring sites in Beijing from January 1, 2016, to December 31, 2017. The experimental results show that the performance of the proposed model is better than other baseline models.<\/jats:p>","DOI":"10.1155\/2021\/1616806","type":"journal-article","created":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T13:38:32Z","timestamp":1634737112000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Research on PM2.5 Spatiotemporal Forecasting Model Based on LSTM Neural Network"],"prefix":"10.1155","volume":"2021","author":[{"given":"Fang","family":"Zhao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyi","family":"Liang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiyan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0921-848X","authenticated-orcid":false,"given":"Dewen","family":"Seng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiyuan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,10,19]]},"reference":[{"key":"e_1_2_10_1_2","doi-asserted-by":"publisher","DOI":"10.1161\/cir.0b013e3181dbece1"},{"key":"e_1_2_10_2_2","first-page":"795","article-title":"Neurogenic inflammation and particulate matter (pm) air pollutants","volume":"22","author":"Veronesi B.","year":"2002","journal-title":"Neurobehavioral Toxicology"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1080\/01926230601059985"},{"key":"e_1_2_10_4_2","article-title":"Long-term pm2.5 exposure and neurological hospital admissions in the northeastern United States","volume":"124","author":"Kioumourtzoglou M. A.","year":"2015","journal-title":"Environmental Health Perspectives"},{"key":"e_1_2_10_5_2","doi-asserted-by":"publisher","DOI":"10.1155\/2012\/782462"},{"key":"e_1_2_10_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2015.02.005"},{"key":"e_1_2_10_7_2","doi-asserted-by":"crossref","unstructured":"ZhengY. YiX. W. LiM. LiR. U. ShanZ. Q. andChangE. Forecasting fine-grained air quality based on big data Proceedings of the 21th SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD \u201815) August 2015 New York NY USA 2267\u20132276 https:\/\/doi.org\/10.1145\/2783258.2788573 2-s2.0-84954159209.","DOI":"10.1145\/2783258.2788573"},{"key":"e_1_2_10_8_2","first-page":"968","article-title":"Advances in research on proinflammatory effects of biochemical components of atmospheric particulate matter","volume":"63","author":"Fangxia S.","year":"2018","journal-title":"Chinese Science Bulletin"},{"key":"e_1_2_10_9_2","doi-asserted-by":"publisher","DOI":"10.1038\/323533a0"},{"key":"e_1_2_10_10_2","doi-asserted-by":"publisher","DOI":"10.18280\/ts.370402"},{"key":"e_1_2_10_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2017.2753802"},{"key":"e_1_2_10_12_2","doi-asserted-by":"publisher","DOI":"10.18280\/ts.370106"},{"key":"e_1_2_10_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/access.2019.2897028"},{"key":"e_1_2_10_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2019.01.333"},{"key":"e_1_2_10_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2018.10.243"},{"key":"e_1_2_10_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2018.11.086"},{"key":"e_1_2_10_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.06.049"},{"key":"e_1_2_10_18_2","article-title":"Time series analysis, forecasting and control","volume":"134","author":"Box G. E. P.","year":"1971","journal-title":"Journal of the American Statistical Association"},{"key":"e_1_2_10_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/s0968-090x(02)00009-8"},{"key":"e_1_2_10_20_2","doi-asserted-by":"publisher","DOI":"10.1080\/15472450902858368"},{"key":"e_1_2_10_21_2","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","volume":"25","author":"Krizhevsky A.","year":"2012","journal-title":"News in Physiological Sciences"},{"key":"e_1_2_10_22_2","doi-asserted-by":"crossref","unstructured":"GravesA. MohamedA. R. andHintonG. Speech recognition with deep recurrent neural networks Proceedings of the 2013 IEEE International Conference on Acoustics Speech and Signal Processing May 2013 Vancouver BC Canada 6645\u20136649 https:\/\/doi.org\/10.1109\/icassp.2013.6638947 2-s2.0-84890543083.","DOI":"10.1109\/ICASSP.2013.6638947"},{"key":"e_1_2_10_23_2","unstructured":"LeQ. V.andMikolovT. Distributed representations of sentences and documents 32 Proceedings of the 31th International Conference on Machine Learning June 2014 Beijing China no. 2 1188\u20131196."},{"key":"e_1_2_10_24_2","unstructured":"SutskeverI. VinyalsO. andLeQ. V. Sequence to sequence learning with neural networks 2014 https:\/\/arxiv.org\/abs\/1409.3215v3."},{"key":"e_1_2_10_25_2","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_2_10_26_2","doi-asserted-by":"crossref","unstructured":"ChoK. Van MerrienboerB. GulcehreC. BahdanauD. BougaresF. andSchwenkH. Learning phrase representations using RNN encoder-decoder for statistical machine translation 2014 https:\/\/arxiv.org\/abs\/1406.1078v3.","DOI":"10.3115\/v1\/D14-1179"},{"key":"e_1_2_10_27_2","doi-asserted-by":"publisher","DOI":"10.1029\/2002jd003179"},{"key":"e_1_2_10_28_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2004.01.039"},{"key":"e_1_2_10_29_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2006.04.044"},{"key":"e_1_2_10_30_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2008.07.020"},{"key":"e_1_2_10_31_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2011.02.001"},{"key":"e_1_2_10_32_2","first-page":"240","article-title":"Note on regression and inheritance in the case of two parents","volume":"58","author":"Pearson K.","year":"2006","journal-title":"Proceedings of the Royal Society of London"},{"key":"e_1_2_10_33_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.envpol.2017.08.114"},{"key":"e_1_2_10_34_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aej.2020.12.009"}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2021\/1616806.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2021\/1616806.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2021\/1616806","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T11:29:33Z","timestamp":1722943773000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2021\/1616806"}},"subtitle":[],"editor":[{"given":"Yassine","family":"Maleh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":34,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1155\/2021\/1616806"],"URL":"https:\/\/doi.org\/10.1155\/2021\/1616806","archive":["Portico"],"relation":{},"ISSN":["1687-5265","1687-5273"],"issn-type":[{"value":"1687-5265","type":"print"},{"value":"1687-5273","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"2021-05-17","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-08-27","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-10-19","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"1616806"}}