Machine Learning Decision Support Model for Greenhouse Gas Reduction Technology Application

I. Aliev

2022

Abstract

Many countries have implemented policies to reduce greenhouse gas (GHG) emissions since the 21st Conference of the Parties (COP 21) of the United Nations Framework Convention on Climate Change (UNFCCC) in 2015. The parties to this convention have voluntarily agreed to a new climate regime that aims to reduce greenhouse gas emissions. Subsequently, reducing greenhouse gas emissions through specific reduction technologies (renewable energy) to reduce energy consumption has become a necessity rather than an option. With the launch of the Korea Emissions Trading Scheme (K-ETS) in 2015, Korea has certified and funded projects to reduce greenhouse gas emissions. To help the user make informed decisions about the economic and environmental benefits of using renewable energy, an evaluation model has been developed. This study establishes a simple assessment method (SAM), an assessment database (DB) of 1199 greenhouse gas reduction technologies implemented in Korea, and a machine learning-based greenhouse gas reduction technology assessment model (GRTM). In addition, proposals are made to assess the economic benefits that can be obtained in combination with the environmental benefits of technology to reduce greenhouse gas emissions.

Paper Citation

in Harvard Style

Aliev I. (2022). Machine Learning Decision Support Model for Greenhouse Gas Reduction Technology Application. In Proceedings of the 1st International Conference on Methods, Models, Technologies for Sustainable Development - Volume 1: MMTGE, ISBN 978-989-758-608-8, SciTePress, pages 165-168. DOI: 10.5220/0011556700003524

in Bibtex Style

@conference{mmtge22,
author={I. Aliev},
title={Machine Learning Decision Support Model for Greenhouse Gas Reduction Technology Application},
booktitle={Proceedings of the 1st International Conference on Methods, Models, Technologies for Sustainable Development - Volume 1: MMTGE,},
year={2022},
pages={165-168},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011556700003524},
isbn={978-989-758-608-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Methods, Models, Technologies for Sustainable Development - Volume 1: MMTGE,
TI - Machine Learning Decision Support Model for Greenhouse Gas Reduction Technology Application
SN - 978-989-758-608-8
AU - Aliev I.
PY - 2022
SP - 165
EP - 168
DO - 10.5220/0011556700003524
PB - SciTePress