{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T22:41:58Z","timestamp":1780353718529,"version":"3.54.1"},"reference-count":36,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/OAPA.html"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology of Taiwan and Academia Sinica","doi-asserted-by":"publisher","award":["MOST 105-2221-E-001-016-MY3"],"award-info":[{"award-number":["MOST 105-2221-E-001-016-MY3"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology of Taiwan and Academia Sinica","doi-asserted-by":"publisher","award":["MOST 106-3114-E-001-004"],"award-info":[{"award-number":["MOST 106-3114-E-001-004"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology of Taiwan and Academia Sinica","doi-asserted-by":"publisher","award":["AS-104-SS-A02"],"award-info":[{"award-number":["AS-104-SS-A02"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2018]]},"DOI":"10.1109\/access.2018.2820164","type":"journal-article","created":{"date-parts":[[2018,3,28]],"date-time":"2018-03-28T18:20:08Z","timestamp":1522261208000},"page":"19193-19204","source":"Crossref","is-referenced-by-count":75,"title":["Improving the Accuracy and Efficiency of PM2.5 Forecast Service Using Cluster-Based Hybrid Neural Network Model"],"prefix":"10.1109","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9558-8895","authenticated-orcid":false,"given":"Sachit","family":"Mahajan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao-Min","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tzu-Chieh","family":"Tsai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5667-7764","authenticated-orcid":false,"given":"Ling-Jyh","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref33","author":"hyndman","year":"2014","journal-title":"Forecasting Principles and Practice"},{"key":"ref32","doi-asserted-by":"crossref","first-page":"109","DOI":"10.3390\/en9020109","article-title":"Wind speed prediction using a univariate ARIMA model and a multivariate NARX model","volume":"9","author":"cadenas","year":"2016","journal-title":"Energies"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.techfore.2010.01.009"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1097\/EDE.0000000000000269"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/2938559.2938560"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/S0925-2312(01)00702-0"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/UIC-ATC.2017.8397443"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2007.01.092"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2013.10.046"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1155\/2015\/785061"},{"key":"ref13","year":"2018","journal-title":"PM2 5 Open Data Portal"},{"key":"ref14","first-page":"948","article-title":"Dimension reduction using semi-supervised locally linear embedding for plant leaf classification","author":"zhang","year":"2009","journal-title":"Proc Int Conf Intell Comput"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2015.09.028"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2016.11.004"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788573"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783275"},{"key":"ref19","first-page":"41","article-title":"Using machine learning to estimate global PM2.5 for environmental health studies","volume":"9","author":"lary","year":"2015","journal-title":"Environ Health Insights"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph13090921"},{"key":"ref4","article-title":"An overview of air pollution problem in megacities and city clusters in China","author":"tang","year":"2007","journal-title":"AGU Spring Meeting Abstracts"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2007.10.044"},{"key":"ref3","first-page":"69","article-title":"The impact of PM2.5 on the human respiratory system","volume":"8","author":"xing","year":"2016","journal-title":"Thoracic Diseases"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"186","DOI":"10.3390\/w9030186","article-title":"Use of meta-heuristic techniques in rainfall-runoff modelling","volume":"9","author":"chau","year":"2017","journal-title":"WATER"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph120606608"},{"key":"ref5","year":"2013","journal-title":"Vietnam Named among Top Ten Nations with Worst Air Pollution"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2015.08.008"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.2166\/hydro.2013.134"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2822885"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.2478\/v10216-011-0022-y"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2013.2296516"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/2629592"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2488188"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s11356-016-7812-9"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/APPEEC.2011.5748446"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2012.01.006"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.7763\/IJESD.2015.V6.648"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2009.932254"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8274985\/08327574.pdf?arnumber=8327574","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T06:04:52Z","timestamp":1643177092000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/8327574\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/access.2018.2820164","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]}}}