Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/201243
Type: Artigo de periódico
Title: Classification Of Diesel Pool Refinery Streams Through Near Infrared Spectroscopy And Support Vector Machines Using C-svc And ν-svc.
Author: Alves, Julio Cesar L
Henriques, Claudete B
Poppi, Ronei J
Abstract: The use of near infrared (NIR) spectroscopy combined with chemometric methods have been widely used in petroleum and petrochemical industry and provides suitable methods for process control and quality control. The algorithm support vector machines (SVM) has demonstrated to be a powerful chemometric tool for development of classification models due to its ability to nonlinear modeling and with high generalization capability and these characteristics can be especially important for treating near infrared (NIR) spectroscopy data of complex mixtures such as petroleum refinery streams. In this work, a study on the performance of the support vector machines algorithm for classification was carried out, using C-SVC and ν-SVC, applied to near infrared (NIR) spectroscopy data of different types of streams that make up the diesel pool in a petroleum refinery: light gas oil, heavy gas oil, hydrotreated diesel, kerosene, heavy naphtha and external diesel. In addition to these six streams, the diesel final blend produced in the refinery was added to complete the data set. C-SVC and ν-SVC classification models with 2, 4, 6 and 7 classes were developed for comparison between its results and also for comparison with the soft independent modeling of class analogy (SIMCA) models results. It is demonstrated the superior performance of SVC models especially using ν-SVC for development of classification models for 6 and 7 classes leading to an improvement of sensitivity on validation sample sets of 24% and 15%, respectively, when compared to SIMCA models, providing better identification of chemical compositions of different diesel pool refinery streams.
Subject: Algorithms
Industrial Waste
Petroleum
Spectroscopy, Near-infrared
Support Vector Machines
Classification
Diesel Pool Streams
Near Infrared Spectroscopy
Support Vector Machines
Rights: fechado
Identifier DOI: 10.1016/j.saa.2013.08.018
Address: http://www.ncbi.nlm.nih.gov/pubmed/24012979
Date Issue: 2014
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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