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Energy consumption, economic growth, and CO2 emissions in G20 countries: Application of adaptive neuro-fuzzy inference system

Understanding the relationships among CO2 emissions, energy consumption, and economic growth helps nations to develop energy sources and formulate energy policies in order to enhance sustainable development. The present research is aimed at developing a novel efficient model for analyzing the relati...

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Main Author: Mardani, Abbas
Format: Article
Language:English
Published: MDPI AG 2018
Subjects:
H Social Sciences (General)
Q Science (General)
Online Access:http://eprints.utm.my/id/eprint/86584/1/AbbasMardani2018_EnergyConsumptionEconomicGrowthandCO2Emissions.pdf
http://eprints.utm.my/id/eprint/86584/
http://dx.doi.org/10.3390/en11102771
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spelling my.utm.865842020-09-30T08:43:51Z http://eprints.utm.my/id/eprint/86584/ Energy consumption, economic growth, and CO2 emissions in G20 countries: Application of adaptive neuro-fuzzy inference system Mardani, Abbas H Social Sciences (General) Q Science (General) Understanding the relationships among CO2 emissions, energy consumption, and economic growth helps nations to develop energy sources and formulate energy policies in order to enhance sustainable development. The present research is aimed at developing a novel efficient model for analyzing the relationships amongst the three aforementioned indicators in G20 countries using an adaptive neuro-fuzzy inference system (ANFIS) model in the period from 1962 to 2016. In this regard, the ANFIS model has been used with prediction models using real data to predict CO2 emissions based on two important input indicators, energy consumption and economic growth. This study made use of the fuzzy rules through ANFIS to generalize the relationships of the input and output indicators in order to make a prediction of CO2 emissions. The experimental findings on a real-world dataset of World Development Indicators (WDI) revealed that the proposed model efficiently predicted the CO2 emissions based on energy consumption and economic growth. The direction of the interrelationship is highly important from the economic and energy policy-making perspectives for this international forum, as G20 countries are primarily focused on the governance of the global economy. MDPI AG 2018-10 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/86584/1/AbbasMardani2018_EnergyConsumptionEconomicGrowthandCO2Emissions.pdf Mardani, Abbas (2018) Energy consumption, economic growth, and CO2 emissions in G20 countries: Application of adaptive neuro-fuzzy inference system. Energies, 11 (10). pp. 1-15. ISSN 1996-1073 http://dx.doi.org/10.3390/en11102771 DOI:10.3390/en11102771
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic H Social Sciences (General)
Q Science (General)
spellingShingle H Social Sciences (General)
Q Science (General)
Mardani, Abbas
Energy consumption, economic growth, and CO2 emissions in G20 countries: Application of adaptive neuro-fuzzy inference system
description Understanding the relationships among CO2 emissions, energy consumption, and economic growth helps nations to develop energy sources and formulate energy policies in order to enhance sustainable development. The present research is aimed at developing a novel efficient model for analyzing the relationships amongst the three aforementioned indicators in G20 countries using an adaptive neuro-fuzzy inference system (ANFIS) model in the period from 1962 to 2016. In this regard, the ANFIS model has been used with prediction models using real data to predict CO2 emissions based on two important input indicators, energy consumption and economic growth. This study made use of the fuzzy rules through ANFIS to generalize the relationships of the input and output indicators in order to make a prediction of CO2 emissions. The experimental findings on a real-world dataset of World Development Indicators (WDI) revealed that the proposed model efficiently predicted the CO2 emissions based on energy consumption and economic growth. The direction of the interrelationship is highly important from the economic and energy policy-making perspectives for this international forum, as G20 countries are primarily focused on the governance of the global economy.
format Article
author Mardani, Abbas
author_facet Mardani, Abbas
author_sort Mardani, Abbas
title Energy consumption, economic growth, and CO2 emissions in G20 countries: Application of adaptive neuro-fuzzy inference system
title_short Energy consumption, economic growth, and CO2 emissions in G20 countries: Application of adaptive neuro-fuzzy inference system
title_full Energy consumption, economic growth, and CO2 emissions in G20 countries: Application of adaptive neuro-fuzzy inference system
title_fullStr Energy consumption, economic growth, and CO2 emissions in G20 countries: Application of adaptive neuro-fuzzy inference system
title_full_unstemmed Energy consumption, economic growth, and CO2 emissions in G20 countries: Application of adaptive neuro-fuzzy inference system
title_sort energy consumption, economic growth, and co2 emissions in g20 countries: application of adaptive neuro-fuzzy inference system
publisher MDPI AG
publishDate 2018
url http://eprints.utm.my/id/eprint/86584/1/AbbasMardani2018_EnergyConsumptionEconomicGrowthandCO2Emissions.pdf
http://eprints.utm.my/id/eprint/86584/
http://dx.doi.org/10.3390/en11102771
_version_ 1680321067324801024
score 13.223943

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