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Predicting future hourly residential electrical consumption: A machine learning case study
Predicting future hourly residential electrical consumption: A machine learning case study
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Predicting future hourly residential electrical consumption: A machine learning case study

Edwards, Richard E. ; New, Joshua ; Parker, Lynne E.

Energy and buildings, 2012-06, Vol.49, p.591-603 [Periódico revisado por pares]

Oxford: Elsevier B.V

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2
Potential benefits of cool walls on residential and commercial buildings across California and the United States: Conserving energy, saving money, and reducing emission of greenhouse gases and air pollutants
Potential benefits of cool walls on residential and commercial buildings across California and the United States: Conserving energy, saving money, and reducing emission of greenhouse gases and air pollutants
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Potential benefits of cool walls on residential and commercial buildings across California and the United States: Conserving energy, saving money, and reducing emission of greenhouse gases and air pollutants

Rosado, Pablo J. ; Levinson, Ronnen

Energy and buildings, 2019-09, Vol.199 (C), p.588-607 [Periódico revisado por pares]

Lausanne: Elsevier B.V

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3
Investigating Primary Factors Affecting Electricity Consumption in Non-Residential Buildings Using a Data-Driven Approach
Investigating Primary Factors Affecting Electricity Consumption in Non-Residential Buildings Using a Data-Driven Approach
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Investigating Primary Factors Affecting Electricity Consumption in Non-Residential Buildings Using a Data-Driven Approach

Cho, Sooyoun ; Lee, Jeehang ; Baek, Jumi ; Kim, Gi-Seok ; Leigh, Seung-Bok

Energies (Basel), 2019-10, Vol.12 (21), p.4046 [Periódico revisado por pares]

Basel: MDPI AG

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4
Effects of Working from Home on Greenhouse Gas Emissions and the Associated Energy Costs in Six Australian Cities
Effects of Working from Home on Greenhouse Gas Emissions and the Associated Energy Costs in Six Australian Cities
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Effects of Working from Home on Greenhouse Gas Emissions and the Associated Energy Costs in Six Australian Cities

Navaratnam, Satheeskumar ; Jayalath, Amitha ; Aye, Lu

Buildings (Basel), 2022-04, Vol.12 (4), p.463 [Periódico revisado por pares]

Basel: MDPI AG

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5
Analysis of a Residential Building Energy Consumption as “Base Model” in Tripoli, Lebanon
Analysis of a Residential Building Energy Consumption as “Base Model” in Tripoli, Lebanon
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Analysis of a Residential Building Energy Consumption as “Base Model” in Tripoli, Lebanon

Yathreb, S.

International journal of energy production and management, 2016-11, Vol.1 (4), p.359-370 [Periódico revisado por pares]

Southampton: W I T Press

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6
Ten questions concerning occupant behavior in buildings: The big picture
Ten questions concerning occupant behavior in buildings: The big picture
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Ten questions concerning occupant behavior in buildings: The big picture

Hong, Tianzhen ; Yan, Da ; D'Oca, Simona ; Chen, Chien-fei

Building and environment, 2017-03, Vol.114, p.518-530 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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7
Planning for sustainable cities by estimating building occupancy with mobile phones
Planning for sustainable cities by estimating building occupancy with mobile phones
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Planning for sustainable cities by estimating building occupancy with mobile phones

Barbour, Edward ; Davila, Carlos Cerezo ; Gupta, Siddharth ; Reinhart, Christoph ; Kaur, Jasleen ; González, Marta C

Nature communications, 2019-08, Vol.10 (1), p.3736-10, Article 3736 [Periódico revisado por pares]

England: Nature Publishing Group

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8
Measures to improve energy demand flexibility in buildings for demand response (DR): A review
Measures to improve energy demand flexibility in buildings for demand response (DR): A review
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Measures to improve energy demand flexibility in buildings for demand response (DR): A review

Chen, Yongbao ; Xu, Peng ; Gu, Jiefan ; Schmidt, Ferdinand ; Li, Weilin

Energy and buildings, 2018-10, Vol.177, p.125-139 [Periódico revisado por pares]

Lausanne: Elsevier B.V

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9
Future climate change and building energy demand in Tianjin, China
Future climate change and building energy demand in Tianjin, China
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Future climate change and building energy demand in Tianjin, China

Li, Mingcai ; Guo, Jun ; Tian, Zhe ; Shi, Jun ; Xiong, Mingming ; Xiang, Cao

Building services engineering research & technology, 2014-07, Vol.35 (4), p.362-375 [Periódico revisado por pares]

London, England: SAGE Publications

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10
Intelligent buildings: An overview
Intelligent buildings: An overview
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Intelligent buildings: An overview

Mofidi, Farhad ; Akbari, Hashem

Energy and buildings, 2020-09, Vol.223, p.110192, Article 110192 [Periódico revisado por pares]

Lausanne: Elsevier B.V

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