Quantitative analysis of chiral compounds from unresolved peaks in capillary electrophoresis using multivariate calibration with experimental design and artificial neural networks

Chirality ◽  
2002 ◽  
Vol 14 (6) ◽  
pp. 509-518 ◽  
Author(s):  
Vlastimil Dohnal ◽  
Hua Li ◽  
Marta Farková ◽  
Josef Havel
Keyword(s):  
Neural Networks ◽  
Capillary Electrophoresis ◽  
Artificial Neural Networks ◽  
Quantitative Analysis ◽  
Experimental Design ◽  
Multivariate Calibration ◽  
Chiral Compounds ◽  
Artificial Neural

Establish an Artificial Neural Networks Model to Make Quantitative Analysis about the Capillary Electrophoresis Spectrum

2012 ◽  
Vol 452-453 ◽  
pp. 1116-1120
Author(s):  
Hong Ping Li ◽  
Hong Li
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Capillary Electrophoresis ◽  
Artificial Neural Networks ◽  
Quantitative Analysis ◽  
Network Model ◽  
Neural Network Model ◽  
Network Training ◽  
Dissociation Degree ◽  
Artificial Neural

Simulating the overlapping capillary electrophoresis spectrogram under the dissimilar conditions by the computer system , Choosing the overlapping capillary electrophoresis spectrogram simulated under the different conditions , processing the data to compose a neural network training regulations, Applying the artificial neural networks method to make a quantitative analysis about the multi-component in the overlapping capillary electrophoresis spectrogram,Using: Radial direction primary function neural network model and multi-layered perceptron neural network model. The findings indicated that, along with the increasing of the capillary electrophoresis spectrogram noise level, the related components’ ability of the two kinds of the overlapping capillary electrophoresis spectrogram by neural network model quantitative analysis drop down. Along with the increasing of the capillary electrophoresis spectrogram’s total dissociation degree, the multi-layered perceptron neural network model to the related components’ ability of the overlapping capillary electrophoresis spectum by quantitative analysis raise up.

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