Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 45,
  • Issue 4,
  • pp. 713-714
  • (1991)

Carbon Number Prediction from Herschel-Infrared Spectra Using Partial Least-Squares Regression

Not Accessible

Your library or personal account may give you access

Abstract

In the accompanying note, we pointed out the potential usefulness of the Herschel-infrared (∼700–1100 nm) for solvent measurements, particularly for process measurements over optical fibers and with filter photometers. In this note we demonstrate that multivariate mathematics can be used to extract even more information, which would be difficult or impossible to obtain directly from the spectra. The subtle differences in the spectra of a homologous series of <i>n</i>-alkanes allowed us to use partial least-squares regression (PLS) to model and predict the carbon chain length of the alkanes.

PDF Article
More Like This
Partial least squares regression calculation for quantitative analysis of metals submerged in water measured using laser-induced breakdown spectroscopy

Tomoko Takahashi, Blair Thornton, Takumi Sato, Toshihiko Ohki, Koichi Ohki, and Tetsuo Sakka
Appl. Opt. 57(20) 5872-5883 (2018)

Acidity measurement of iron ore powders using laser-induced breakdown spectroscopy with partial least squares regression

Z.Q. Hao, C.M. Li, M. Shen, X.Y. Yang, K.H. Li, L.B. Guo, X.Y. Li, Y.F. Lu, and X.Y. Zeng
Opt. Express 23(6) 7795-7801 (2015)

Cited By

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

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.