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Application of Artificial Intelligence in Sugar Production Forecasting in the State of São Paulo

Grant number: 23/05265-4
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): July 01, 2023
Effective date (End): June 30, 2024
Field of knowledge:Interdisciplinary Subjects
Principal Investigator:Marilaine Colnago
Grantee:Lucas Alexandre Borges de Matos
Host Institution: Instituto de Química (IQ). Universidade Estadual Paulista (UNESP). Campus de Araraquara. Araraquara , SP, Brazil

Abstract

Sugarcane plays a crucial role in the Brazilian economy. The country is the world's largest producer, and 55% of the planted area located in the state of São Paulo. The state is also the largest producer of sugar in Brazil, accounting for about 60% of the national production and approximately 30% of the world's production. Given the economic and social importance of this scenario, the study of mathematical models and computational methods that seek to analyze sugar production may become essential to support important decisions made by government agencies, local consumers, and sectors of the agriculture, energy, or sugarcane byproducts market industry. Therefore, this project aims to study sugar production in the state of São Paulo using Machine Learning (ML) models and Exploratory Data Analysis (EDA) tools. For the research, two ML methodologies will be explored: Random Forest and Artificial Neural Networks (ANNs). The models will be coded and validated based on real ethanol production databases in the state, whose computational framework to be developed could serve to improve the sugarcane byproducts industry sector.

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