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Type: Artigo de periódico
Title: Application Of Artificial Neural Networks To The Classification Of Soils From São Paulo State Using Near-infrared Spectroscopy
Author: Fidencio P.H.
Ruisanchez I.
Poppi R.J.
Abstract: This paper describes how artificial neural networks can be used to classify multivariate data. Two types of neural networks were applied: a counter propagation neural network (CP-ANN) and a radial basis function network (RBFN). These strategies were used to classify soil samples from different geographical regions in Brazil by means of their near-infrared (diffuse reflectance) spectra. The results were better with CP-ANN (classification error 8.6%) than with RBFN (classification error 11.0%).
Rights: aberto
Identifier DOI: 10.1039/b107533k
Date Issue: 2001
Appears in Collections:Unicamp - Artigos e Outros Documentos

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