By Topic

Improvement of Prediction Ability of Multicomponent Regression Model by a Method Based on Data Mining in Chemometrics

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ling Gao ; Dept. of Chem., Inner Mongolia Univ., Huhhot ; Shouxin Ren

A novel method named OSCWPTPLS approach based on partial least squares (PLS) regression with orthogonal signal correction (OSC) and wavelet packet transform (WPT) as preprocessed tools was proposed for the simultaneous spectrophotometric determination of Al(III), Mn(II) and Co(II). 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. In this case, using trials, the kind of wavelet function, the decomposition level, the number of OSC components and the number of PLS factors for the OSCWPTPLS method were selected as Daubechies 4, 3, 2 and 3, respectively. A program (POSCWPTPLS) was designed to perform the simultaneous spectrophotometric determination of Al(III), Mn(II) and Co(II). The relative standard errors of prediction (RSEP) obtained for all components using OSCWPTPLS, WPTPLS and PLS were compared. Experimental results demonstrated that the OSCWPTPLS method had the best performance among the three methods and was successful even when there was severe overlap of spectra.

Published in:

Knowledge Discovery and Data Mining, 2009. WKDD 2009. Second International Workshop on

Date of Conference:

23-25 Jan. 2009