LAPSE:2023.24470
Published Article
LAPSE:2023.24470
Understanding Household Fuel Choice Behaviour in the Amazonas State, Brazil: Effects of Validation and Feature Selection
March 28, 2023
Since 2003, Brazil has striven to provide energy access to all, in rural areas, in an effort to economically empower the communities. Unpacking fuel stacking behaviour can shed light onto the speed of transition toward the exclusive use of advanced fuel types. This paper presents findings from surveys that were carried out with 14 non-electrified communities in a rural area of Rio Negro, Amazonas State, Brazil. We identify the fuel choice determinants in these communities using a multinomial logistic regression model and more generally discuss the validity and robustness of such models in the context of statistical validation and evaluation metrics. Specifically for the Amazonas communities considered in this study, the research showed that the fuel choice determinants are the age of household, the number of people at meals each day, the number of meals daily, the community, education of the household head, and the income level of the household. Moreover, given the Brazilian policies related to energy and sustainability, this region is not likely to reach the Sustainable Development Goals proposed by United Nations for 2030.
Keywords
fuel choice, fuel stacking, multinomial logistic regression model, rural electrification
Suggested Citation
Gyamfi KS, Gaura E, Brusey J, Trindade AB, Verba N. Understanding Household Fuel Choice Behaviour in the Amazonas State, Brazil: Effects of Validation and Feature Selection. (2023). LAPSE:2023.24470
Author Affiliations
Gyamfi KS: Centre for Data Science, Coventry University, Coventry CV1 5FB, UK [ORCID]
Gaura E: Centre for Data Science, Coventry University, Coventry CV1 5FB, UK [ORCID]
Brusey J: Centre for Data Science, Coventry University, Coventry CV1 5FB, UK [ORCID]
Trindade AB: Department of Electricity, Federal University of Amazonas (UFAM), AM 69067-005 Manaus, Brazil [ORCID]
Verba N: Centre for Data Science, Coventry University, Coventry CV1 5FB, UK [ORCID]
Journal Name
Energies
Volume
13
Issue
15
Article Number
E3857
Year
2020
Publication Date
2020-07-28
Published Version
ISSN
1996-1073
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PII: en13153857, Publication Type: Journal Article
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LAPSE:2023.24470
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doi:10.3390/en13153857
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Mar 28, 2023
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