New model for prediction binary mixture of antihistamine decongestant using artificial neural networks and least squares support vector machine by spectrophotometry method

In the present study, artificial neural networks (ANNs) and least squares support vector machines (LS-SVM) as intelligent methods based on absorption spectra in the range of 230‐300nm have been used for determination of antihistamine decongestant contents. In the first step, one type of network (fee...

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Veröffentlicht in:	Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jg. 182; S. 105 - 115
Hauptverfasser:	Mofavvaz, Shirin, Sohrabi, Mahmoud Reza, Nezamzadeh-Ejhieh, Alireza
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Elsevier B.V 05.07.2017
Schlagworte:	Algorithms Antihistamine decongestant Artificial neural networks Backpropagation GDX algorithm, least square support vector machine Histamine Antagonists - analysis Lavenberg-Marquardt algorithm Least-Squares Analysis Linear Models Nasal Decongestants - analysis Neural Networks (Computer) Reproducibility of Results Sensitivity and Specificity Spectrophotometric Spectrophotometry - methods Support Vector Machine Backpropagation GDX algorithm, least square support vector machine Spectrophotometric Antihistamine decongestant Lavenberg-Marquardt algorithm Artificial neural networks
ISSN:	1386-1425, 1873-3557, 1873-3557
Online-Zugang:	Volltext
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