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Predicting Research and Motor Octane Numbers Based on Near Infrared Spectroscopy: Models Based on Partial Least Squares Regression and Artificial Neural Networks

AuthID
P-00P-HJT

Author(s)

Leal, AL

Ribeiro, JC

Silva, AMS

Martins, FG

Editor(s)

Friedl, A; Klemes, JJ; Radl, S; Varbanov, PS; Wallek, T

Document Type

Proceedings Paper

Year published

2018

Published

in 28TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING in Computer Aided Chemical Engineering, ISSN: 1570-7946

Volume: 43, Pages: 187-192 (6)

Conference

28Th European Symposium on Computer-Aided Process Engineering (Escape), Date: JUN 10-13, 2018, Location: Graz, AUSTRIA, Sponsors: European Federat Chem Engn, CAPE Working Party, TU Graz, TU Wien, Brno Univ Technol, Sci Coordinat Team

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Publication Identifiers

DOI: 10.1016/b978-0-444-64235-6.50034-6

Wos: WOS:000441374200034

Source Identifiers

ISSN: 1570-7946

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Predicting Research and Motor Octane Numbers Based on Near Infrared Spectroscopy: Models Based on Partial Least Squares Regression and Artificial Neural Networks

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