Assess the local electricity consumption: the case of Reunion island through a GIS based method Article Swipe

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Fiona Bénard , Jean-Philippe Praene , Yatina Calixte ·

YOU? · · 2018 · Open Access · · DOI: https://doi.org/10.3934/energy.2018.3.436

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Electricity

Environmental Economics

Electrical Engineering

Mechanical Engineering

Archaeology

Machine Learning

Social Science

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Electricity Environmental economics Consumption (sociology) Energy consumption Work (physics) Value (mathematics) Efficient energy use Business Typology Computer science Geography Economics Engineering Electrical engineering Mechanical engineering Sociology Archaeology Machine learning Social science

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Type: article
Language: en
Landing Page: https://doi.org/10.3934/energy.2018.3.436
OA Status: gold
Cited By: 3
References: 29
Related Works: 10
OpenAlex ID: https://openalex.org/W2805031817

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OpenAlex ID: https://openalex.org/W2805031817

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DOI: https://doi.org/10.3934/energy.2018.3.436

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Title: Assess the local electricity consumption: the case of Reunion island through a GIS based method

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Type: article

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Language: en

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Publication year: 2018

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Publication date: 2018-01-01

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Authors: Fiona Bénard, Jean-Philippe Praene, Yatina Calixte

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Landing page: https://doi.org/10.3934/energy.2018.3.436

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OA status: gold

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OA URL: https://doi.org/10.3934/energy.2018.3.436

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Concepts: Electricity, Environmental economics, Consumption (sociology), Energy consumption, Work (physics), Value (mathematics), Efficient energy use, Business, Typology, Computer science, Geography, Economics, Engineering, Electrical engineering, Mechanical engineering, Sociology, Archaeology, Machine learning, Social science

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Cited by: 3

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Citations by year (recent): 2023: 1, 2020: 1, 2018: 1

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References (count): 29

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Related works (count): 10

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sustainable_development_goals[0].score	0.47999998927116394
sustainable_development_goals[0].display_name	Affordable and clean energy
citation_normalized_percentile.value	0.48133767
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	False