The Role of Energy Consumption and Economic Growth on Carbon Emission: Application of Artificial Neural Network

Hemant Kumar Sah; Gyanendra Singh Sisodia; Gouher Ahmed; Aqila Rafiuddin; Naseem Abidi

doi:10.32479/ijeep.14666

The Role of Energy Consumption and Economic Growth on Carbon Emission: Application of Artificial Neural Network

Hemant Kumar Sah
, Gyanendra Singh Sisodia
, Gouher Ahmed
, Aqila Rafiuddin
, Naseem Abidi

College of Business Administration

Alliance University
Skyline University College
Birla Institute of Technology and Science Pilani
Instituto Tecnologico de Estudios Superiores de Monterrey

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

This paper examines the influence of gross domestic product (GDP) and energy consumption (renewable energy and non-renewable energy) on carbon emissions in European Union (EU) Countries use of panel data from 2000 to 2020. By using Artificial Neural Network (ANN) machine learning computational technique, variables are categorized into input and output parameters. The result from the analyses shows that RMSE values of all variables are significant. Further, the normalized importance obtained from the multilayer perception ANN algorithm highlights the importance of variables and their association. The finding suggests that EU countries should adopt a clean energy strategy and policy for environmental protection without compromising economic growth.

Original language	English
Pages (from-to)	591-596
Number of pages	6
Journal	International Journal of Energy Economics and Policy
Volume	13
Issue number	6
DOIs	https://doi.org/10.32479/ijeep.14666
State	Published - 11 Oct 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 8 Decent Work and Economic Growth
SDG 13 Climate Action

Keywords

Artificial Neural Network
Carbon Emission
Energy Consumption
GDP growth

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10.32479/ijeep.14666

Cite this

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title = "The Role of Energy Consumption and Economic Growth on Carbon Emission: Application of Artificial Neural Network",

abstract = "This paper examines the influence of gross domestic product (GDP) and energy consumption (renewable energy and non-renewable energy) on carbon emissions in European Union (EU) Countries use of panel data from 2000 to 2020. By using Artificial Neural Network (ANN) machine learning computational technique, variables are categorized into input and output parameters. The result from the analyses shows that RMSE values of all variables are significant. Further, the normalized importance obtained from the multilayer perception ANN algorithm highlights the importance of variables and their association. The finding suggests that EU countries should adopt a clean energy strategy and policy for environmental protection without compromising economic growth.",

keywords = "Artificial Neural Network, Carbon Emission, Energy Consumption, GDP growth",

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AU - Sah, Hemant Kumar

AU - Sisodia, Gyanendra Singh

AU - Ahmed, Gouher

AU - Rafiuddin, Aqila

AU - Abidi, Naseem

PY - 2023/10/11

Y1 - 2023/10/11

N2 - This paper examines the influence of gross domestic product (GDP) and energy consumption (renewable energy and non-renewable energy) on carbon emissions in European Union (EU) Countries use of panel data from 2000 to 2020. By using Artificial Neural Network (ANN) machine learning computational technique, variables are categorized into input and output parameters. The result from the analyses shows that RMSE values of all variables are significant. Further, the normalized importance obtained from the multilayer perception ANN algorithm highlights the importance of variables and their association. The finding suggests that EU countries should adopt a clean energy strategy and policy for environmental protection without compromising economic growth.

AB - This paper examines the influence of gross domestic product (GDP) and energy consumption (renewable energy and non-renewable energy) on carbon emissions in European Union (EU) Countries use of panel data from 2000 to 2020. By using Artificial Neural Network (ANN) machine learning computational technique, variables are categorized into input and output parameters. The result from the analyses shows that RMSE values of all variables are significant. Further, the normalized importance obtained from the multilayer perception ANN algorithm highlights the importance of variables and their association. The finding suggests that EU countries should adopt a clean energy strategy and policy for environmental protection without compromising economic growth.

KW - Artificial Neural Network

KW - Carbon Emission

KW - Energy Consumption

KW - GDP growth

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JO - International Journal of Energy Economics and Policy

JF - International Journal of Energy Economics and Policy

IS - 6

ER -

The Role of Energy Consumption and Economic Growth on Carbon Emission: Application of Artificial Neural Network

Abstract

UN SDGs

Keywords

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