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Predictive Analysis of Ethanol Production: Modeling and Applications via Computational Intelligence Algorithms

Grant number: 22/15191-5
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): June 01, 2023
Effective date (End): May 31, 2024
Field of knowledge:Engineering - Chemical Engineering
Principal Investigator:Marilaine Colnago
Grantee:Isabela Mendes de Oliveira
Host Institution: Instituto de Química (IQ). Universidade Estadual Paulista (UNESP). Campus de Araraquara. Araraquara , SP, Brazil


Ethanol has been widely considered as an alternative for reducing environmental and energy problems in the world, as it has the advantages of being a renewable source and reducing carbon dioxide emissions. Faced with a growth scenario, at a national level, in ethanol production, the study of mathematical models and computational methods that seek to analyze ethanol production, can become essential to support important decisions, whether they are taken by government agencies, local consumers , or even by sectors of the energy agriculture industry or the biofuels market. Thus, this project aims to study ethanol production in the state of São Paulo using Machine Learning (ML) models and Exploratory Data Analysis (AED) tools. For the development of the research, two MA methodologies will be explored: Random Forests, and Artificial Neural Networks (ANNs). The models will be codified and validated from real databases of ethanol production in the state, whose computational framework to be developed may serve to improve the biofuel sector.

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