Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/60146
Type: Artigo de periódico
Title: Inference of the biodiesel cetane number by multivariate techniques
Author: Nadai, DV
Simoes, JB
Gatts, CEN
Miranda, PCML
Abstract: In this work, we have implemented a method which uses structural information from H-1 NMR spectra of fatty esters and biodiesels to infer the corresponding Cetane Number (CN). The method consists of the successive application of Principal Component Analysis (PCA), Fuzzy Clustering and a feed-forward Artificial Neural Network (ANN) to the data set. PCA recognized redundant information, and determined the number of clusters for subsequent Fuzzy Clustering classification. At the final stage ANN used membership values from the Fuzzy Clustering process as inputs to predict the cetane number of different types of biodiesel (complex mixtures) from data of pure substances (esters). Root-mean-square deviations were in the range of 0.2-2.4. (C) 2012 Elsevier Ltd. All rights reserved.
Subject: Neural network
Alkyl fatty esters
Cetane number
Fuzzy Clustering
Country: Inglaterra
Editor: Elsevier Sci Ltd
Rights: fechado
Identifier DOI: 10.1016/j.fuel.2012.06.018
Date Issue: 2013
Appears in Collections:Unicamp - Artigos e Outros Documentos

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