Title :
Analyze Overlapping Baker Square Wave Voltammograms Based on Data Mining
Author :
Gao, Ling ; Ren, Shouxin
Author_Institution :
Dept. of Chem., Inner Mongolia Univ., Huhhot, China
Abstract :
A novel method, referred to as OSC-WPT-PLS approach based on partial least squares(PLS) regression with orthogonal signal correction(OSC) and wavelet packet transform (WPT) as preprocessed tools, was proposed to carry out the simultaneous voltammetric determination of Pb(II), Tl(I) and In (III) for the first time. This method combines the ideas of OSC and WPT with PLS regression for enhancing the ability of extracting characteristic information and the quality of regression. The relative standard errors of prediction (RSEP) obtained for all elements using OSC-WPT-PLS, WPT-PLS and PLS were compared. Experimental results demonstrated that the OSC-WPT-PLS method had the best performance among the three methods and was successful even when there was severe overlap of voltammgrams.
Keywords :
chemical engineering computing; data mining; error correction; least mean squares methods; regression analysis; signal processing; voltammetry (chemical analysis); wavelet transforms; OSC; PLS; RSEP; WPT; data mining; orthogonal signal correction; overlapping Baker square wave voltammograms; partial least square regression; relative standard errors of prediction; voltammetric determination; wavelet packet transform; Calibration; Chemical technology; Chemistry; Data analysis; Data mining; Least squares methods; Redundancy; Signal processing; Wavelet packets; Wavelet transforms; data mining; multivariate calibration; orthogonal signal correction; overlapping voltammogram; signal processing; wavelet packet transform;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
DOI :
10.1109/ICICTA.2010.156