dc.creatorContant, S
dc.creatorCarita, G
dc.creatorMachado, PFMPB
dc.creatorLona, LMF
dc.date2010
dc.dateOCT-DEC
dc.date2014-11-17T13:05:35Z
dc.date2015-11-26T16:43:12Z
dc.date2014-11-17T13:05:35Z
dc.date2015-11-26T16:43:12Z
dc.date.accessioned2018-03-28T23:28:07Z
dc.date.available2018-03-28T23:28:07Z
dc.identifierBrazilian Journal Of Chemical Engineering. Brazilian Soc Chemical Eng, v. 27, n. 4, n. 643, n. 651, 2010.
dc.identifier0104-6632
dc.identifierWOS:000286106200016
dc.identifier10.1590/S0104-66322010000400016
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/65964
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/65964
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/65964
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1273524
dc.descriptionBiocides play an important role in the preservation of a variety of products susceptible to microbiological growth such as paint, a material that can undergo microbial deterioration both in storing (inside the can) and after the application on a surface. In this work, artificial neural networks were used to predict the level of fungal growth on surfaces painted with water-based paints with biocide formulations containing different concentrations of ten kinds of commercial and experimental chemical agents. The use of neural networks is well known in chemical processes and they are a powerful tool for discovering relationships between sets of data. Industrial Environmental Tropical Chamber tests were used as the network training set. The importance of the each additive of the dry-film biocide formulation in prevention of biodeterioration was also examined.
dc.description27
dc.description4
dc.description643
dc.description651
dc.languageen
dc.publisherBrazilian Soc Chemical Eng
dc.publisherSao Paulo
dc.publisherBrasil
dc.relationBrazilian Journal Of Chemical Engineering
dc.relationBraz. J. Chem. Eng.
dc.rightsaberto
dc.sourceWeb of Science
dc.subjectNeural networks
dc.subjectBiocide
dc.subjectPaint film
dc.subjectFungal growth
dc.subjectFungal
dc.subjectBuildings
dc.subjectGrowth
dc.subjectDesign
dc.titleEVALUATION OF THE EFFECT OF DRY-FILM BIOCIDES ON PAINT FILM PRESERVATION USING NEURAL NETWORKS
dc.typeArtículos de revistas


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