Coupling The Image Analysis And The Artificial Neural Networks To Predict A Mixing Time Of A Pharmaceutical Powder

dc.contributor.authorMahdi, Y.
dc.contributor.authorMouhi, L.
dc.contributor.authorGuemras, N.
dc.contributor.authorDaoud, K.
dc.date.accessioned2020-10-28T10:47:23Z
dc.date.available2020-10-28T10:47:23Z
dc.date.issued2016-09-01
dc.descriptionArticale in Journal of fundamental and Applied Sciences Vol. 08, N. 03en_US
dc.description.abstractIn recent years, different laboratories were interested in predicting the mixing time of a pharmaceutical powder. In fact, a nonhomogeneous mixture may lead to under dose and/or overdose of the active ingredient in the drug product. Our study is aimed toward using a new and revolutionary approach in the field of the processes “The Artificial Neural Networks” (ANN) by using the Neural Networks ToolboxTM derived from Matlab® software. The validation of the neural network was assumed by studying others mixing powders and then we compared the experimental results to the data obtained by the neural network calculations. Experimental results were obtained from a non-destructive method (Image Analysis) which was used in order to characterize the homogeneity of powder mixture in a V-Blender as well as a Cubic Blender which are most used in the pharmaceutical industry.en_US
dc.identifier.citationArticale in Journal of fundamental and Applied Sciences Vol. 08, N. 03en_US
dc.identifier.issn1112-9867
dc.identifier.urihttps://dspace.univ-eloued.dz/handle/123456789/7358
dc.language.isoenen_US
dc.publisherUniversity of Eloued جامعة الواديen_US
dc.subjectANN; Image analysis; Homogeneity; Back-propagation algorithm; multi-layer perceptronen_US
dc.titleCoupling The Image Analysis And The Artificial Neural Networks To Predict A Mixing Time Of A Pharmaceutical Powderen_US
dc.typeArticleen_US

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