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Statistical-based method to determine the best hour of the ..:
, In:
2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
,
Riekstin, Ana Carolina
;
Hedjam, Rachid
;
Dandrest, Thomas
. - p. 1-8 , 2017
Link:
https://doi.org/10.1109/UIC-ATC.2017.8397428
RT T1 <cTitle>2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)</cTitle>: T1 <Title>Statistical-based method to determine the best hour of the day regarding GHG emissions for a smart home appliance</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-8397428&Exemplar=1&LAN=DE A1 Riekstin, Ana Carolina A1 Hedjam, Rachid A1 Dandrest, Thomas A1 Cheriet, Mohamed YR 2017 K1 Smart Home K1 Emission Factors K1 GHG Emissions K1 Prediction SP 1 OP 8 LK http://dx.doi.org/https://doi.org/10.1109/UIC-ATC.2017.8397428 DO https://doi.org/10.1109/UIC-ATC.2017.8397428 SF ELIB - SuUB Bremen
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