{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T11:14:03Z","timestamp":1730200443137,"version":"3.28.0"},"reference-count":7,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1109\/bigdata.2018.8622559","type":"proceedings-article","created":{"date-parts":[[2019,1,25]],"date-time":"2019-01-25T03:07:18Z","timestamp":1548385638000},"page":"4488-4491","source":"Crossref","is-referenced-by-count":4,"title":["PM2.5 Forecasting Using Pre-trained Components"],"prefix":"10.1109","author":[{"given":"Ming-Chuan","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meng Chang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1006\/jcss.1997.1504"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"1394","DOI":"10.1016\/j.procs.2018.05.068","article-title":"Deepairnet: Applying recurrent networks for air quality prediction","volume":"132","author":"athira","year":"2018","journal-title":"Procedia Computer Science"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-015-1955-3"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783344"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref1","article-title":"An analysis of composite neural network performance from function composition perspective","author":"yang","year":"2018","journal-title":"In submission"}],"event":{"name":"2018 IEEE International Conference on Big Data (Big Data)","start":{"date-parts":[[2018,12,10]]},"location":"Seattle, WA, USA","end":{"date-parts":[[2018,12,13]]}},"container-title":["2018 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8610059\/8621858\/08622559.pdf?arnumber=8622559","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T00:24:33Z","timestamp":1643243073000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8622559\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12]]},"references-count":7,"URL":"https:\/\/doi.org\/10.1109\/bigdata.2018.8622559","relation":{},"subject":[],"published":{"date-parts":[[2018,12]]}}}