Unfolded partial least squares/residual bilinearization combined with the Successive Projections Algorithm for interval selection: enhanced excitation-emission fluorescence data modeling in the presence of the inner filter effect

2015 ◽  
Vol 407 (19) ◽  
pp. 5649-5659 ◽  
Author(s):  
Adriano de Araújo Gomes ◽  
Agustina V. Schenone ◽  
Héctor C. Goicoechea ◽  
Mario Cesar U. de Araújo
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Data Modeling ◽  
Inner Filter Effect ◽  
Successive Projections Algorithm ◽  
Filter Effect ◽  
Interval Selection ◽  
Successive Projections

The Successive Projections Algorithm for interval selection in trilinear partial least-squares with residual bilinearization

2014 ◽  
Vol 811 ◽  
pp. 13-22 ◽  
Author(s):  
Adriano de Araújo Gomes ◽  
Mirta Raquel Alcaraz ◽  
Hector C. Goicoechea ◽  
Mario Cesar U. Araújo
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Successive Projections Algorithm ◽  
Interval Selection ◽  
Successive Projections

The successive projections algorithm for interval selection in partial least squares discriminant analysis

2016 ◽  
Vol 8 (41) ◽  
pp. 7522-7530 ◽  
Author(s):  
David Douglas de Sousa Fernandes ◽  
Valber Elias Almeida ◽  
Licarion Pinto ◽  
Germano Véras ◽  
Roberto Kawakami Harrop Galvão ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Multivariate Calibration ◽  
Successive Projections Algorithm ◽  
Selection Approach ◽  
Interval Selection ◽  
Successive Projections ◽  
Pls Method

This paper proposes a new interval selection approach for PLS-DA modelling, which is developed as an extension of the recently introduced iSPA-PLS method for multivariate calibration.

scholarly journals Vis-NIR spectrometric determination of Brix and sucrose in sugar production samples using kernel partial least squares with interval selection based on the successive projections algorithm

Talanta ◽  
2018 ◽  
Vol 181 ◽  
pp. 38-43 ◽  
Author(s):  
Valber Elias de Almeida ◽  
Adriano de Araújo Gomes ◽  
David Douglas de Sousa Fernandes ◽  
Héctor Casimiro Goicoechea ◽  
Roberto Kawakami Harrop Galvão ◽  
...  
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Sugar Production ◽  
Successive Projections Algorithm ◽  
Kernel Partial Least Squares ◽  
Interval Selection ◽  
Successive Projections

scholarly journals Modeling of inner filter effect in synchronous spectrofluorimetry by using partial least squares

Analusis ◽  
2000 ◽  
Vol 28 (2) ◽  
pp. 148-154 ◽  
Author(s):  
A. Andrade-Eiroa ◽  
E. Vázquez-Blanco ◽  
P. López-Mahía ◽  
S. Muniategui-Lorenzo ◽  
D. Prada-Rodríguez
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Inner Filter Effect ◽  
Synchronous Spectrofluorimetry ◽  
Filter Effect

Determination of fat content in chicken hamburgers using NIR spectroscopy and the Successive Projections Algorithm for interval selection in PLS regression ( i SPA-PLS)

2018 ◽  
Vol 189 ◽  
pp. 300-306 ◽  
Author(s):  
Gabriela Krepper ◽  
Florencia Romeo ◽  
David Douglas de Sousa Fernandes ◽  
Paulo Henrique Gonçalves Dias Diniz ◽  
Mário César Ugulino de Araújo ◽  
...  
Keyword(s):  
Nir Spectroscopy ◽  
Fat Content ◽  
Pls Regression ◽  
Successive Projections Algorithm ◽  
Interval Selection ◽  
Successive Projections

scholarly journals Analysis of Methanol Gasoline by ATR-FT-IR Spectroscopy

2019 ◽  
Vol 9 (24) ◽  
pp. 5336 ◽  
Author(s):  
Qi XIA ◽  
Lei-ming YUAN ◽  
Xiaojing CHEN ◽  
Liuwei MENG ◽  
Guangzao HUANG
Keyword(s):  
Quantitative Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Internal Combustion Engines ◽  
Quantitative Model ◽  
Least Square ◽  
Support Vector ◽  
Least Squares Regression ◽  
Transportation Industry ◽  
Successive Projections Algorithm

Methanol gasoline blends are a more economical, and environmentally friendly fuels than gasoline alone, and are widely used in the transportation industry. The content of methanol in methanol gasoline plays an important role in ensuring the quality of gasoline. In some solutions, due to the shortage of energy and illegal profits, the problem of gasoline adulteration and its fineness, has received more and more attention, which would seriously affect the operating condition and service life of internal combustion engines. Therefore, it is very important to identify the correct level of gasoline. However, the traditional detection method is complex and time-consuming. To this end, the feasibility of using attenuated total reflectance Fourier transform infrared (ATR-FTIR) methods coupled with chemometrics methods were investigated to quantitatively and qualitatively analyze methanol gasoline. The qualitative analysis result of partial least squares discriminant analysis (PLS-DA) obtained 100% and 98.66% accuracy in the calibration set and the prediction set, respectively. As for quantitative analysis; two regression algorithms of partial least squares regression (PLSR) and the least square support vector machine (LS-SVM), as well as two variables selection methods of the successive projections algorithm (UVE) competitive adaptive reweighted sampling (CARS) and uninformative variable elimination (UVE) were combined to establish the quantitative model. By comparing the performance of the optimal models; the UVE-PLSR model performed best with a residual predictive deviation (RPD) value of 6.420. The qualitative and quantitative analysis results demonstrate the feasibility of using ATR-FTIR spectra to detect the methanol in methanol gasoline. It is believed that the promising IR spectra will be widely used in gasoline energy quality control in the further.

Multivariate data modeling using modified kernel partial least squares

2015 ◽  
Vol 94 ◽  
pp. 466-474 ◽  
Author(s):  
Yingbin Gao ◽  
Xiangyu Kong ◽  
Changhua Hu ◽  
Zhengxin Zhang ◽  
Hongzeng Li ◽  
...  
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Multivariate Data ◽  
Data Modeling ◽  
Kernel Partial Least Squares
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