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Using machine learning to select variables in data envelopment analysis: Simulations and application using electricity distribution dataEnergy economics, 2023-04, Vol.120 [Peer Reviewed Journal]ISSN: 0140-9883 ;ISSN: 1873-6181 ;EISSN: 1873-6181 ;DOI: 10.1016/j.eneco.2023.106621Digital Resources/Online E-Resources |
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Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plantsEuropean journal of operational research, 2009-09, Vol.197 (3), p.1095-1105 [Peer Reviewed Journal]ISSN: 0377-2217 ;EISSN: 1872-6860 ;DOI: 10.1016/j.ejor.2007.12.052Digital Resources/Online E-Resources |
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A Spatial Stochastic Frontier Model with Omitted Variables: Electricity Distribution in NorwayThe Energy journal (Cambridge, Mass.), 2018-05, Vol.39 (3), p.93-116 [Peer Reviewed Journal]Copyright © 2018 by the IAEE ;The Author(s) ;Copyright 2018, The International Association for Energy Economics ;ISSN: 0195-6574 ;EISSN: 1944-9089 ;DOI: 10.5547/01956574.39.3.loreFull text available |
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Performance Analysis of Short-Term Electricity Demand with Atmospheric VariablesEnergies (Basel), 2018-04, Vol.11 (4), p.818 [Peer Reviewed Journal]Copyright MDPI AG 2018 ;ISSN: 1996-1073 ;EISSN: 1996-1073 ;DOI: 10.3390/en11040818Full text available |
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Automatic Selection of Temperature Variables for Short-Term Load ForecastingSustainability, 2022-10, Vol.14 (20), p.13339 [Peer Reviewed Journal]COPYRIGHT 2022 MDPI AG ;2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2071-1050 ;EISSN: 2071-1050 ;DOI: 10.3390/su142013339Full text available |
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Material Type: Article
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Pressurised electro-osmotic dewatering of activated and anaerobically digested sludges: electrical variables analysisWater research (Oxford), 2012-09, Vol.46 (14), p.4405 [Peer Reviewed Journal]Copyright © 2012 Elsevier Ltd. All rights reserved. ;EISSN: 1879-2448 ;DOI: 10.1016/j.watres.2012.05.053 ;PMID: 22748325Digital Resources/Online E-Resources |
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The Effect of Feed-in Tariffs on Renewable Electricity Generation: An Instrumental Variables ApproachEnvironmental & resource economics, 2014-03, Vol.57 (3), p.367-392 [Peer Reviewed Journal]Springer Science+Business Media Dordrecht 2013 ;Springer Science+Business Media Dordrecht 2014 ;ISSN: 0924-6460 ;EISSN: 1573-1502 ;DOI: 10.1007/s10640-013-9684-5Full text available |
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Correlation between Weather Variables and Electricity DemandIOP conference series. Earth and environmental science, 2021-12, Vol.927 (1), p.12015 [Peer Reviewed Journal]Published under licence by IOP Publishing Ltd ;2021. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1755-1307 ;EISSN: 1755-1315 ;DOI: 10.1088/1755-1315/927/1/012015Full text available |
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The Influence of Local Environmental, Economic and Social Variables on the Spatial Distribution of Photovoltaic Applications across China’s Urban AreasEnergies (Basel), 2018-08, Vol.11 (8), p.1986 [Peer Reviewed Journal]2018. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1996-1073 ;EISSN: 1996-1073 ;DOI: 10.3390/en11081986Full text available |
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Material Type: Article
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Electricity energy dataset “BanE-16”: Analysis of peak energy demand with environmental variables for machine learning forecastingData in brief, 2024-02, Vol.52, p.109967-109967, Article 109967 [Peer Reviewed Journal]2023 The Author(s) ;2023 The Author(s). ;2023 The Author(s) 2023 ;ISSN: 2352-3409 ;EISSN: 2352-3409 ;DOI: 10.1016/j.dib.2023.109967 ;PMID: 38235179Full text available |
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Causalities between CO2, electricity, and other energy variables during phase I and phase II of the EU ETSEnergy policy, 2010-07, Vol.38 (7), p.3329-3341 [Peer Reviewed Journal]ISSN: 0301-4215 ;EISSN: 1873-6777 ;DOI: 10.1016/j.enpol.2010.02.004Digital Resources/Online E-Resources |
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Development of Scientific Reasoning Test Measuring Control of Variables Strategy in Physics for High School Students: Evidence of Validity and Latent Predictors of Item DifficultyInternational journal of science education, 2021-09, Vol.43 (13), p.2185 [Peer Reviewed Journal]ISSN: 0950-0693 ;EISSN: 1464-5289 ;DOI: 10.1080/09500693.2021.1957515Digital Resources/Online E-Resources |
13 |
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Modeling arbitrage of an energy storage unit without binary variablesCSEE Journal of Power and Energy Systems, 2021-01, Vol.7 (1), p.156-161 [Peer Reviewed Journal]2021. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://ieeexplore.ieee.org/Xplorehelp/#/accessing-content/open-access. ;ISSN: 2096-0042 ;EISSN: 2096-0042 ;DOI: 10.17775/CSEEJPES.2019.03340Full text available |
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Determinants of Variables That Affect Electrical Energy Consumption in Indonesia 2011-2020International journal of energy economics and policy, 2024-01, Vol.14 (1), p.165-1712024. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2146-4553 ;EISSN: 2146-4553 ;DOI: 10.32479/ijeep.11069Full text available |
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Material Type: Article
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Cluster Analysis of Residential Personal Exposure to ELF Magnetic Field in Children: Effect of Environmental VariablesInternational journal of environmental research and public health, 2019-11, Vol.16 (22), p.4363 [Peer Reviewed Journal]2019. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2019 by the authors. 2019 ;ISSN: 1660-4601 ;ISSN: 1661-7827 ;EISSN: 1660-4601 ;DOI: 10.3390/ijerph16224363 ;PMID: 31717366Full text available |
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The Sensitivity of an Electro-Thermal Photovoltaic DC–DC Converter Model to the Temperature Dependence of the Electrical Variables for Reliability AnalysesEnergies (Basel), 2020-06, Vol.13 (11), p.2865 [Peer Reviewed Journal]2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1996-1073 ;EISSN: 1996-1073 ;DOI: 10.3390/en13112865Full text available |
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Material Type: Article
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SERVQUAL model with extended variables of safety awareness and energy conservation: impact on consumer satisfaction with mediating and moderating effectInternational journal of energy sector management, 2024-05, Vol.18 (4), p.857-872 [Peer Reviewed Journal]Emerald Publishing Limited. ;ISSN: 1750-6220 ;EISSN: 1750-6220 ;EISSN: 1750-6239 ;DOI: 10.1108/IJESM-04-2023-0010Digital Resources/Online E-Resources |
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A Hybrid Model for Electricity Demand Forecast Using Improved Ensemble Empirical Mode Decomposition and Recurrent Neural Networks with ERA5 Climate VariablesEnergies (Basel), 2022-10, Vol.15 (19), p.7434 [Peer Reviewed Journal]COPYRIGHT 2022 MDPI AG ;2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1996-1073 ;EISSN: 1996-1073 ;DOI: 10.3390/en15197434Full text available |
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Material Type: Article
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Methodological development for the optimisation of electricity cost in cement factories: the use of artificial intelligence in process variablesElectrical engineering, 2022-06, Vol.104 (3), p.1681-1696 [Peer Reviewed Journal]The Author(s) 2021 ;ISSN: 0948-7921 ;EISSN: 1432-0487 ;DOI: 10.1007/s00202-021-01409-zDigital Resources/Online E-Resources |
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Material Type: Article
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Meteorological Variables’ Influence on Electric Power Generation for Photovoltaic Systems Located at Different Geographical Zones in MexicoApplied sciences, 2019-04, Vol.9 (8), p.1649 [Peer Reviewed Journal]2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2076-3417 ;EISSN: 2076-3417 ;DOI: 10.3390/app9081649Full text available |