OSA's Digital Library

Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 51, Iss. 7 — Mar. 1, 2012
  • pp: B108–B114

Construction of a predictive model for concentration of nickel and vanadium in vacuum residues of crude oils using artificial neural networks and LIBS

José L. Tarazona, Jáder Guerrero, Rafael Cabanzo, and E. Mejía-Ospino  »View Author Affiliations


Applied Optics, Vol. 51, Issue 7, pp. B108-B114 (2012)
http://dx.doi.org/10.1364/AO.51.00B108


View Full Text Article

Enhanced HTML    Acrobat PDF (253 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

A predictive model to determine the concentration of nickel and vanadium in vacuum residues of Colombian crude oils using laser-induced breakdown spectroscopy (LIBS) and artificial neural networks (ANNs) with nodes distributed in multiple layers (multilayer perceptron) is presented. ANN inputs are intensity values in the vicinity of the emission lines 300.248, 301.200 and 305.081 nm of the Ni(I), and 309.310, 310.229, and 311.070 nm of the V(II). The effects of varying number of nodes and the initial weights and biases in the ANNs were systematically explored. Average relative error of calibration/prediction (REC/REP) and average relative standard deviation (RSD) metrics were used to evaluate the performance of the ANN in the prediction of concentrations of two elements studied here.

© 2012 Optical Society of America

OCIS Codes
(020.0020) Atomic and molecular physics : Atomic and molecular physics
(300.0300) Spectroscopy : Spectroscopy

History
Original Manuscript: September 26, 2011
Revised Manuscript: December 1, 2011
Manuscript Accepted: December 14, 2011
Published: February 24, 2012

Citation
José L. Tarazona, Jáder Guerrero, Rafael Cabanzo, and E. Mejía-Ospino, "Construction of a predictive model for concentration of nickel and vanadium in vacuum residues of crude oils using artificial neural networks and LIBS," Appl. Opt. 51, B108-B114 (2012)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-51-7-B108

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Log in to access OSA Member Subscription

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Log in to access OSA Member Subscription

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Log in to access OSA Member Subscription

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Log in to access OSA Member Subscription

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited