Integrating a partial least squares model with an artificial neural network to discriminate FTIR spectra of virus infected vero cells at 6 hours post exposure

2011 ◽  
Author(s):  
J. A. Ward ◽  
C. Filfili ◽  
Ruli Wang ◽  
G. Hastings ◽  
Jing Guo ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Least Squares ◽  
Partial Least Squares ◽  
Vero Cells ◽  
Ftir Spectra ◽  
Post Exposure ◽  
Partial Least Squares Model ◽  
Artificial Neural

A partial least squares and artificial neural network study for a series of arylpiperazines as antidepressant agents

2021 ◽  
Vol 27 (10) ◽  
Author(s):  
Genisson R. Santos ◽  
Laise P. A. Chiari ◽  
Aldineia P. da Silva ◽  
Célio F. Lipinski ◽  
Aline A. Oliveira ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Least Squares ◽  
Partial Least Squares ◽  
Antidepressant Agents ◽  
Artificial Neural

scholarly journals Visible and Near-Infrared Multispectral Features in Conjunction with Artificial Neural Network and Partial Least Squares for Predicting Biochemical and Micro-Structural Features of Beef Muscles

Foods ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1254
Author(s):  
Abderrahmane Aït-Kaddour ◽  
Donato Andueza ◽  
Annabelle Dubost ◽  
Jean-Michel Roger ◽  
Jean-François Hocquette ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Multispectral Imaging ◽  
Structural Features ◽  
Ann Model ◽  
Practical Applications ◽  
Artificial Neural

The objective of this study was to determine the potential of multispectral imaging (MSI) data recorded in the visible and near infrared electromagnetic regions to predict the structural features of intramuscular connective tissue, the proportion of intramuscular fat (IMF), and some characteristic parameters of muscle fibers involved in beef sensory quality. In order to do this, samples from three muscles (Longissimus thoracis, Semimembranosus and Biceps femoris) of animals belonging to three breeds (Aberdeen Angus, Limousine, and Blonde d’Aquitaine) were used (120 samples). After the acquisition of images by MSI and segmentation of their morphological parameters, a back propagation artificial neural network (ANN) model coupled with partial least squares was applied to predict the muscular parameters cited above. The results presented a high accuracy and are promising (R2 test > 0.90) for practical applications. For example, considering the prediction of IMF, the regression model giving the best ANN model exhibited R2P = 0.99 and RMSEP = 0.103 g × 100 g−1 DM.

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