Public Energy Management in Brazil: Decision Analysis and Machine Learning

Fabricio Quadros Borges; Bruno Alencar da Costa; Inaldo de Souza Sampaio Filho; Marlis Elena Ramírez Requelme; João Paulo Abreu Almeida

doi:10.34257/GJHSSBVOL23IS1PG1

Authors

Fabricio Quadros Borges
Bruno Alencar da Costa
Inaldo de Souza Sampaio Filho
Marlis Elena Ramírez Requelme
João Paulo Abreu Almeida

Keywords:

planning; sustainability; electricity

Abstract

The analyzes carried out by artificial intelligence must start from a complete and integrated data structure, which is classified and grouped with the intention of synergistically producing mental and predictive captures. In this perspective, the objective of this study is to analyze the possibility of contribution of artificial intelligence in guiding decision-making in the public planning of sustainable electrical matrices. The methodological procedures of this investigation, built a structure of analysis of electricity sources, based on the economic, social, environmental and technological dimensions; as well as a sectoral analysis structure of energy sustainability indicators, supported by linear correlations of an economic, social, environmental and political nature. The planning of electrical matrices, according to the inferences of this investigation, can use artificial intelligence as a strategic guide for decisions, as long as they are based on analysis structures focused on the strategic use of electricity sources and the use of sectoral and multidimensional indicators.

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How to Cite

Public Energy Management in Brazil: Decision Analysis and Machine Learning. (2023). Global Journal of Human-Social Science, 23(B1), 1-11. https://doi.org/10.34257/GJHSSBVOL23IS1PG1

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