Verification of the performance of Artificial Neural Networks (ANNs) versus Partial Least Squares (PLS) for spectral interference correction in optical emission spectrometry-Reference-Cited by-同舟云学术

Verification of the performance of Artificial Neural Networks (ANNs) versus Partial Least Squares (PLS) for spectral interference correction in optical emission spectrometry

Published:2014-05-22 Issue: Volume: Page:
ISSN:0277-786X
Container-title:SPIE Proceedings
language:
Short-container-title:

Author:

Li Z.,Zhang X.,Karanassios V.

Publisher

SPIE

Reference77 articles.

1. Bringing part of the lab to the field: On-site chromium speciation in seawater by electrodeposition of Cr(III)/Cr(VI) on portable coiled-filament assemblies and measurement in the lab by electrothermal, near-torch vaporization sample introduction and inductively coupled plasma-atomic emission spectrometry

2. Micro- and nano-volume samples by electrothermal, near-torch vaporization sample introduction using removable, interchangeable and portable rhenium coiled-filament assemblies and axially-viewed inductively coupled plasma-atomic emission spectrometry

3. Taking part of the lab to the sample: On-site electrodeposition of Pb followed by measurement in a lab using electrothermal, near-torch vaporization sample introduction and inductively coupled plasma-atomic emission spectrometry

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