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A COMBINATION OF NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHMS FOR SOLVING THE OPTIMIZATION PROBLEMS IN PHARMACEUTICS

Le Hoai Bac 1
Hoang Kiem 1
Do Quang Duong 2
Volume & Issue: Vol. 6 No. 5&6 (2003) | Page No.: 5-12 | DOI: 10.32508/stdj.v6i5&6.3324
Published: 2003-06-30

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Copyright The Author(s) 2023. This article is published with open access by Vietnam National University, Ho Chi Minh city, Vietnam. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0) which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. 

Abstract

In the pharmaceutical market, all products have a life cycle and out-of-date products should be improved or innovated by new ones. For this reason, design and optimization of formulation are the regular demands. Traditional methods of design and optimization - such as statistics, simplex, ... - have only used for simple and linear data. In the event that data is complicated and non-linear, these methods are not suitably. This paper presents a solution for optimizing formulation and process of production in pharmaceutics by combining of AI technics: neural networks, fuzzy logic and genetic algorithms. This solution helps pharmacist save a lot of time and labor because of its accuracy and processing speed.

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