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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-10-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/11/10/2771 |
| _version_ | 1811308221727506432 |
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| author | Abbas Mardani Dalia Streimikiene Mehrbakhsh Nilashi Daniel Arias Aranda Nanthakumar Loganathan Ahmad Jusoh |
| author_facet | Abbas Mardani Dalia Streimikiene Mehrbakhsh Nilashi Daniel Arias Aranda Nanthakumar Loganathan Ahmad Jusoh |
| author_sort | Abbas Mardani |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-13T09:18:19Z |
| format | Article |
| id | doaj.art-d6019ccbbfd04ef7b8c82dd70804d9e5 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-13T09:18:19Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-d6019ccbbfd04ef7b8c82dd70804d9e52022-12-22T02:52:41ZengMDPI AGEnergies1996-10732018-10-011110277110.3390/en11102771en11102771Energy Consumption, Economic Growth, and CO2 Emissions in G20 Countries: Application of Adaptive Neuro-Fuzzy Inference SystemAbbas Mardani0Dalia Streimikiene1Mehrbakhsh Nilashi2Daniel Arias Aranda3Nanthakumar Loganathan4Ahmad Jusoh5Azman Hashim International Business School, Universiti Teknologi Malaysia (UTM), Skudai Johor 81310, MalaysiaLithuanian Institute of Agrarian Economics, V. Kudirkos g. 18-2, 03105 Vilnius, LithuaniaFaculty Computing, Universiti Teknologi Malaysia (UTM), Skudai Johor 81310, MalaysiaDepartment of Business Administration, Faculty of Economic and Business Sciences, University of Granada, 18071 Granada, SpainAzman Hashim International Business School, Universiti Teknologi Malaysia (UTM), Skudai Johor 81310, MalaysiaAzman Hashim International Business School, Universiti Teknologi Malaysia (UTM), Skudai Johor 81310, MalaysiaUnderstanding 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.http://www.mdpi.com/1996-1073/11/10/2771energyCO2growthadaptive neuro-fuzzy inference system (ANFIS) |
| spellingShingle | Abbas Mardani Dalia Streimikiene Mehrbakhsh Nilashi Daniel Arias Aranda Nanthakumar Loganathan Ahmad Jusoh Energy Consumption, Economic Growth, and CO2 Emissions in G20 Countries: Application of Adaptive Neuro-Fuzzy Inference System Energies energy CO2 growth adaptive neuro-fuzzy inference system (ANFIS) |
| title | 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_short | 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 |
| topic | energy CO2 growth adaptive neuro-fuzzy inference system (ANFIS) |
| url | http://www.mdpi.com/1996-1073/11/10/2771 |
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