Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/94828
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%).
Editor: 
Rights: aberto
Identifier DOI: 10.1039/b107533k
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-0035667315&partnerID=40&md5=566b0f90610e000eaf436e436f63e8e4
Date Issue: 2001
Appears in Collections:Unicamp - Artigos e Outros Documentos

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