Simultaneous Spectrophotometric Determination of Cobalt and Nickel by Partial Least Square Regression in Micellar Media

2007 ◽  
Vol 97 (3-4) ◽  
pp. 237-249 ◽  
Author(s):  
Varinder Kaur ◽  
Ashok Kumar Malik ◽  
Neelam Verma
Keyword(s):  
Spectrophotometric Determination ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Micellar Media ◽  
Least Square Regression ◽  
Cobalt And Nickel

scholarly journals Spectrophotometric determination of phenol in the presence of congeners by multivariated calibration

2001 ◽  
Vol 73 (4) ◽  
pp. 519-524 ◽  
Author(s):  
KELY VIVIANE DE SOUZA ◽  
PATRICIO PERALTA-ZAMORA
Keyword(s):  
Spectrophotometric Determination ◽  
Multivariate Calibration ◽  
Close Correlation ◽  
Degradation Process ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Calibration Model ◽  
Transient Species

The generation of poly-hydroxilated transient species during the photochemical treatment of phenol usually impedes the spectrophotmetric monitoring of its degradation process. Frequently, the appearance of compounds such as pyrocatechol, hydroquinone and benzoquinone produces serious spectral interference, which hinder the use of the classical univariate calibration process. In this work, the use of multivariate calibration is proposed to permit the spectrophotometric determination of phenol in the presence of these intermediates. Using 20 synthetic mixtures containing phenol and the interferents, a calibration model was developed by using a partial least square regression process (PLSR) and processing the absorbance signal between 180 and 300 nm. The model was validated by using 3 synthetic mixtures. In this operation, typical errors lower than 3% were observed. Close correlation between the results obtained by liquid chromatography and the proposed method was also observed.

Application of MALDI-TOFMS Combined with Partial Least Square Regression for the Determination of Mercury and Copper in Canned Tuna, Using Dithizone as the Complexing Agent and Ag(I) as Internal Standard

2018 ◽  
Vol 11 (10) ◽  
pp. 2835-2846 ◽  
Author(s):  
Manuel Mendez Garcia ◽  
Kazimierz Wrobel ◽  
Alejandra Sarahi Ramirez Segovia ◽  
Eunice Yanez Barrientos ◽  
Alma Rosa Corrales Escobosa ◽  
...  
Keyword(s):  
Internal Standard ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Complexing Agent ◽  
Canned Tuna ◽  
Least Square Regression

Mechanical Parameter Analysis of Rock Material via PLSR Model

2011 ◽  
Vol 467-469 ◽  
pp. 1826-1831 ◽  
Author(s):  
Zao Bao Liu ◽  
Wei Ya Xu ◽  
Fei Xu ◽  
Lin Wei Wang
Keyword(s):  
Regression Model ◽  
Principal Component ◽  
Partial Least Square ◽  
Rock Material ◽  
Least Square ◽  
Parameter Analysis ◽  
Partial Least Square Regression ◽  
Mechanical Parameter ◽  
Least Square Regression

Mechanical parameter analysis is a complicated issue since it is influenced by many factors. Closely related with the influencing factors of compressibility coefficients of rock material (sandstone), this article first introduces the way to process partial least square regression (PLSR) analysis. The process of carrying out PLSR is divided into six steps as for analysis and prediction of the regression model, which are data preparation, principle collection, regression model for first principle component, secondary principle analysis, establishment of final regression model and number determination of principal component l. And then introduces PLSR for application of analysis and prediction of compressibility coefficients with 30 experiment samples. Seven prediction samples are carried out by PLSR with the training process of 30 samples. The result shows PLSR has good accuracy in prediction under the condition that the model is properly deprived based on certain experimental samples. Finally, some conclusions are made for further study on both mechanical parameters and partial least square regression method.

Sign in / Sign up

Export Citation Format

Share Document