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Comparison of Different PLS Algorithms for Simultaneous Determination of Cd(II), Cu(II), Pb(II), and Zn(II) by Anodic Stripping Voltammetry at Bismuth Film Electrode
Author(s) -
Pinto Licarion,
Lemos Sherlan G.
Publication year - 2014
Publication title -
electroanalysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 128
eISSN - 1521-4109
pISSN - 1040-0397
DOI - 10.1002/elan.201300500
Subject(s) - partial least squares regression , anodic stripping voltammetry , bismuth , stripping (fiber) , voltammetry , analytical chemistry (journal) , chemistry , interval (graph theory) , selection (genetic algorithm) , feature selection , algorithm , electrode , materials science , mathematics , computer science , chromatography , electrochemistry , statistics , artificial intelligence , organic chemistry , composite material , combinatorics
Abstract In this work we evaluated the use of different variable selection techniques combined with partial least‐squares regression (PLS) – genetic algorithm PLS (GA‐PLS), interval PLS (iPLS), and synergy interval PLS (siPLS) – in the simultaneous determination of Cd(II), Cu(II), Pb(II) and Zn(II) by anodic stripping voltammetry at a bismuth film. Generally, variable selection provided an improvement in prediction results when compared to full‐voltammogram PLS. The use of interval selection based algorithms have shown to be most adequate than the selection of discrete variables by GA. Excellent analytical performances were obtained despite the inherent complexity of the simultaneous determination.