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Use of artificial neural networks for the estimation of impurities in mixtures of sugarcane, soil and plant material

Grant number: 18/03690-1
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): July 01, 2018
Effective date (End): June 30, 2020
Field of knowledge:Interdisciplinary Subjects
Principal Investigator:Erica Regina Filletti Nascimento
Grantee:Lucas Janoni dos Santos
Host Institution: Instituto de Química (IQ). Universidade Estadual Paulista (UNESP). Campus de Araraquara. Araraquara , SP, Brazil

Abstract

We propose the development of Artificial Neural Networks (RNAS) as an alternative tool to estimate the fraction of impurities in mixtures of sugarcane, soil and plant material, from digital images of samples of these mixtures in different proportions. The ability to learn through examples and generalize the information learned is undoubtedly the main attraction of problem solving through ANNs. Generalization, which is associated with the ability of the neural network to learn through a reduced set of examples and then give coherent answers to unknown data, is a demonstration that the ability of ANNs goes far beyond simply mapping input ratios and output. Due to these advantages, this tool will be very useful for the study of impurities in the sugarcane, and may bring a possible solution for the characterization of the raw material delivered to the mills. (AU)

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