Developing a machine learning algorithm to investigate the role of energy consumption in sustainable development: A case study of China

DOI

10.2991/978-94-6463-262-0_20How to use a DOI?

Keywords

Machine learning; Energy consumption; Renewable energy; Sustainable development; Guangdong; China

Abstract

Nowadays, the power and strengths of machine learning methodologies encourage all decision-makers to use the benefits of these approaches in their policy planning. The increasing complexity of economic planning in terms of various impactful factors and targets necessitates the comprehensive analysis of influential parameters in economic development using developed machine learning methods. While considering limited factors in economic investigations lead us to unreal conclusions, in this study, five indicators are considered (Total Energy Consumption, Birth Rate, Wastewater Treatment Rate, Number of Repairs Enterprises, and Number of Existing Environment and Public Facilities Management Enterprises) to represent circular economy, social, environmental and energy consumption aspects of sustainable development, respectively. A modern machine-learning algorithm, named XGBoost, had been developed to investigate the impact of mentioned indicators on the sustainable development of the study region. According to panel data of Guangdong Province, China, from 2010 to 2019, the findings state that the circular economy has the top priority in sustainable development. The repairing and reusing of resources as a circular economy solution greatly impact sustainable development. Based on these results, some policy recommendations are provided for appropriate economic development considering social and environmental issues in Guangdong Province.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ali Hashemizadeh
AU  - Faezeh Zareian Baghdad Abadi
PY  - 2023
DA  - 2023/10/09
TI  - Developing a machine learning algorithm to investigate the role of energy consumption in sustainable development: A case study of China
BT  - Proceedings of the 3rd International Conference on Management Science and Software Engineering (ICMSSE 2023)
PB  - Atlantis Press
SP  - 170
EP  - 177
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-262-0_20
DO  - 10.2991/978-94-6463-262-0_20
ID  - Hashemizadeh2023
ER  -