{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T18:00:38Z","timestamp":1775325638660,"version":"3.50.1"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001804","name":"Canada Research Chairs","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001804","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Sustain. Comput."],"published-print":{"date-parts":[[2020,1,1]]},"DOI":"10.1109\/tsusc.2018.2886164","type":"journal-article","created":{"date-parts":[[2018,12,10]],"date-time":"2018-12-10T19:20:38Z","timestamp":1544469638000},"page":"134-146","source":"Crossref","is-referenced-by-count":30,"title":["Time Series-Based GHG Emissions Prediction for Smart Homes"],"prefix":"10.1109","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9340-5995","authenticated-orcid":false,"given":"Ana Carolina","family":"Riekstin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5837-1475","authenticated-orcid":false,"given":"Antoine","family":"Langevin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6999-8468","authenticated-orcid":false,"given":"Thomas","family":"Dandres","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9484-7218","authenticated-orcid":false,"given":"Ghyslain","family":"Gagnon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5246-7265","authenticated-orcid":false,"given":"Mohamed","family":"Cheriet","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1016\/j.energy.2014.01.059","article-title":"Influence of wind power on hourly electricity prices and GHG (greenhouse gas) emissions: Evidence that congestion matters from Ontario zonal data","volume":"66","author":"amor","year":"2014","journal-title":"Energy"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2017.8030373"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1021\/acs.est.5b05216"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/PESGM.2016.7741759"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2010.01.010"},{"key":"ref30","first-page":"85","article-title":"Multivariate regression tree for pattern-based forecasting time series with multiple seasonal cycles","author":"dudek","year":"2017","journal-title":"Proc Int Conf Inf Syst Archit Technol"},{"key":"ref37","year":"2018"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.2991\/ict4s-14.2014.35"},{"key":"ref35","first-page":"1","article-title":"Electric vehicle smart charging aims for $CO_2$CO2 emission reduction?","author":"tikka","year":"2016","journal-title":"Proc IEEE PES Innovative Smart Grid Technol Conf Eur"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2016.12.143"},{"key":"ref28","article-title":"Vector autoregressions","author":"hyndman","year":"2013","journal-title":"Forecasting Principles and Practice"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2002.804943"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.eneco.2015.05.014"},{"key":"ref2","article-title":"Energy use data handbook tables - total end-use sector.","year":"2018"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2017.05.091"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2015.04.003"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ISGTEurope.2011.6162805"},{"key":"ref21","article-title":"Real-time environmental assessment of electricity use: A tool for sustainable demand-side management programs","author":"milovanoff","year":"2017","journal-title":"Int J Life Cycle Assessment"},{"key":"ref24","article-title":"Modeling and forecasting short-term electricity load using regression analysis","author":"hinman","year":"2009","journal-title":"Journal of IInstitute for Regulatory Policy Studies []"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2016.03.089"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2010.12.009"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1002\/tee.22050"},{"key":"ref50","first-page":"2825","article-title":"Scikit-learn: Machine learning in python","volume":"12","author":"pedregosa","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2013.130711"},{"key":"ref56","article-title":"PVWatts calculator version 6.","year":"2017"},{"key":"ref55","first-page":"119","article-title":"PVWATTS-an online performance calculator for grid-connected PV systems","author":"marion","year":"2000","journal-title":"Proc Solar Conf"},{"key":"ref54","article-title":"Home charging calculator.","year":"2017"},{"key":"ref53","article-title":"Smart* data set for sustainability.","author":"repository","year":"2017"},{"key":"ref52","article-title":"Smart*: An open data set and tools for enabling research in sustainable homes","author":"barker","year":"2012","journal-title":"Proc SustKDD Workshop Data Mining Appl Sustainability"},{"key":"ref10","year":"2018"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/UIC-ATC.2017.8397428"},{"key":"ref40","article-title":"Covenant of mayors for climate and energy: Default emission factors for local emission inventories","author":"koffi","year":"2017"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/FUTURETECH.2010.5482712"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s00287-012-0665-9"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2016.03.047"},{"key":"ref15","article-title":"Energy optimizations for smart buildings and smart grids","volume":"491","author":"mishra","year":"2015"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCCN.2016.7568516"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2013.6531113"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2015.06.036"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2012.2220385"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.egypro.2015.12.196"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1080\/15325008.2013.832439"},{"key":"ref6","article-title":"SMARTer2030, ICT Solutions for 21st Century Challenges","year":"2015","journal-title":"Belgium GeSI Accenture Strategy"},{"key":"ref5","article-title":"Towards zero-emission efficient and resilient buildings: Global status report","author":"dean","year":"2016","journal-title":"Global Alliance Buildings Construction (GABC)"},{"key":"ref8","year":"2018"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2015.11.027"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2440-0"},{"key":"ref9","year":"2017"},{"key":"ref46","article-title":"SGDR: Stochastic gradient descent with restarts","author":"loshchilov","year":"2016","journal-title":"CoRR"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298878"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2011.tm09771"},{"key":"ref47","article-title":"SciPy: Open source scientific tools for Python","author":"jones","year":"2001"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2005.06.042"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref44","first-page":"194","article-title":"LSTM neural networks for language modeling","author":"sundermeyer","year":"2012","journal-title":"Proc Annu Conf Int Speech Commun Assoc"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6638947"}],"container-title":["IEEE Transactions on Sustainable Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7274860\/9027020\/08571275.pdf?arnumber=8571275","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T12:34:11Z","timestamp":1651062851000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8571275\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,1]]},"references-count":56,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tsusc.2018.2886164","relation":{},"ISSN":["2377-3782","2377-3790"],"issn-type":[{"value":"2377-3782","type":"electronic"},{"value":"2377-3790","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1,1]]}}}