Preprint Article Version 1 This version is not peer-reviewed

Current Status Investigation and Predicting Carbon Dioxide Emission in Latin American Countries by Connectionist Models

Version 1 : Received: 3 May 2019 / Approved: 6 May 2019 / Online: 6 May 2019 (11:43:56 CEST)

A peer-reviewed article of this Preprint also exists.

Ahmadi, M.H.; Dehghani Madvar, M.; Sadeghzadeh, M.; Rezaei, M.H.; Herrera, M.; Shamshirband, S. Current Status Investigation and Predicting Carbon Dioxide Emission in Latin American Countries by Connectionist Models. Energies 2019, 12, 1916. Ahmadi, M.H.; Dehghani Madvar, M.; Sadeghzadeh, M.; Rezaei, M.H.; Herrera, M.; Shamshirband, S. Current Status Investigation and Predicting Carbon Dioxide Emission in Latin American Countries by Connectionist Models. Energies 2019, 12, 1916.

Journal reference: Energies 2019, 12, 1916
DOI: 10.3390/en12101916

Abstract

Nowadays, one of the biggest concern of human being is greenhouse gas emission, especially carbon dioxide emission in developed and under-developing countries. In this study, connectionist models including LSSVM (Least Square Support Vector Machine) and evolutionary methods are employed for predicting the amount of CO2 emission in six Latin American countries, i.e., Brazil, Mexico, Argentina, Peru, Chile, Venezuela, and Uruguay. The studied region is modelled based on the available input data in terms of Million tons including oil (Million tons), gas (Million tons oil equivalent), coal (Million tons oil equivalent), $R_{ew}$ (Million tons oil equivalent), and Gross Domestic Product (GDP) in terms of billion US dollars.} Moreover, the available patents in the fields of climate change mitigation in six Latin American countries namely Brazil, Mexico, Argentina, Peru, Chile, Venezuela, and Uruguay has been reviewed and analyzed. The results show that except Venezuela, all other mentioned countries have invested in renewable energy R&D activities. Brazil and Argentina have the highest share of renewable energies which account for 60% and 72% respectively.

Subject Areas

CO2; modeling; environment; South America; connectionist model

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