Document Detail


Application of artificial intelligent tools to modeling of glucosamine preparation from exoskeleton of shrimp.
MedLine Citation:
PMID:  19016101     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The objective of this study was to forecast and optimize the glucosamine production yield from chitin (obtained from Persian Gulf shrimp) by means of genetic algorithm (GA), particle swarm optimization (PSO), and artificial neural networks (ANNs) as tools of artificial intelligence methods. Three factors (acid concentration, acid solution to chitin ratio, and reaction time) were used as the input parameters of the models investigated. According to the obtained results, the production yield of glucosamine hydrochloride depends linearly on acid concentration, acid solution to solid ratio, and time and also the cross-product of acid concentration and time and the cross-product of solids to acid solution ratio and time. The production yield significantly increased with an increase of acid concentration, acid solution ratio, and reaction time. The production yield is inversely related to the cross-product of acid concentration and time. It means that at high acid concentrations, the longer reaction times give lower production yields. The results revealed that the average percent error (PE) for prediction of production yield by GA, PSO, and ANN are 6.84, 7.11, and 5.49%, respectively. Considering the low PE, it might be concluded that these models have a good predictive power in the studied range of variables and they have the ability of generalization to unknown cases.
Authors:
Hadi Valizadeh; Mohammad Pourmahmood; Javid Shahbazi Mojarrad; Mahboob Nemati; Parvin Zakeri-Milani
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Drug development and industrial pharmacy     Volume:  35     ISSN:  1520-5762     ISO Abbreviation:  Drug Dev Ind Pharm     Publication Date:  2009 Apr 
Date Detail:
Created Date:  2009-03-16     Completed Date:  2009-05-25     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7802620     Medline TA:  Drug Dev Ind Pharm     Country:  United States    
Other Details:
Languages:  eng     Pagination:  396-407     Citation Subset:  IM    
Affiliation:
Department of Pharmaceutics, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran. valizadeh@tbzmed.ac.ir
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Animals
Chitin / chemistry
Computer Simulation
Expert Systems
Forecasting
Glucosamine / chemistry*
Models, Biological*
Neural Networks (Computer)*
Penaeidae / chemistry*
Solutions
Chemical
Reg. No./Substance:
0/Solutions; 1398-61-4/Chitin; 3416-24-8/Glucosamine

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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