Energy Consumption, Economic Growth, and CO 2 Emissions in G20 Countries: Application of Adaptive Neuro-Fuzzy Inference System

Abbas Mardani, Dalia Streimikiene, Mehrbakhsh Nilashi, Daniel Arias Aranda, Nanthakumar Loganathan and Ahmad Jusoh
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Dalia Streimikiene: Lithuanian Institute of Agrarian Economics, V. Kudirkos g. 18-2, 03105 Vilnius, Lithuania
Mehrbakhsh Nilashi: Faculty Computing, Universiti Teknologi Malaysia (UTM), Skudai Johor 81310, Malaysia
Daniel Arias Aranda: Department of Business Administration, Faculty of Economic and Business Sciences, University of Granada, 18071 Granada, Spain
Ahmad Jusoh: Azman Hashim International Business School, Universiti Teknologi Malaysia (UTM), Skudai Johor 81310, Malaysia

Energies, 2018, vol. 11, issue 10, 1-15

Abstract: Understanding the relationships among CO 2 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 CO 2 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 CO 2 emissions. The experimental findings on a real-world dataset of World Development Indicators (WDI) revealed that the proposed model efficiently predicted the CO 2 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.

Keywords: energy; CO 2; growth; adaptive neuro-fuzzy inference system (ANFIS) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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