Modeling thermal conductivity, specific Heat, and density of milk: A neural network approach

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorFederal University of Viçosa-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorMattar, Henrique L.-
Autor(es): dc.creatorMinim, Luis A.-
Autor(es): dc.creatorCoimbra, Jane S. R.-
Autor(es): dc.creatorMinim, Valéria P. R.-
Autor(es): dc.creatorSaraiva, Sérgio H.-
Autor(es): dc.creatorTelis-Romero, Javier-
Data de aceite: dc.date.accessioned2025-08-21T21:18:57Z-
Data de disponibilização: dc.date.available2025-08-21T21:18:57Z-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2004-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1081/JFP-200032964-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/225452-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/225452-
Descrição: dc.descriptionThe accurate determination of thermophysical properties of milk is very important for design, simulation, optimization, and control of food processing such as evaporation, heat exchanging, spray drying, and so forth. Generally, polynomial methods are used for prediction of these properties based on empirical correlation to experimental data. Artificial neural networks are better suited for processing noisy and extensive knowledge indexing. This article proposed the application of neural networks for prediction of specific heat, thermal conductivity, and density of milk with temperature ranged from 2.0 to 71.0°C, 72.0 to 92.0% of water content (w/w), and 1.350 to 7.822% of fat content (w/w). Artificial neural networks presented a better prediction capability of specific heat, thermal conductivity, and density of milk than polynomial modeling. It showed a reasonable alternative to empirical modeling for thermophysical properties of foods.-
Descrição: dc.descriptionDepartment of Food Technology Federal University of Viçosa, Viçosa, MG-
Descrição: dc.descriptionDepartment of Food Technology UNESP, São José do Rio, Preto, São Paulo-
Descrição: dc.descriptionDepartment of Food Technology UNESP, São José do Rio, Preto, São Paulo-
Formato: dc.format531-539-
Idioma: dc.languageen-
Relação: dc.relationInternational Journal of Food Properties-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectMilk-
Palavras-chave: dc.subjectModeling-
Palavras-chave: dc.subjectNeural network-
Palavras-chave: dc.subjectThermophysical properties-
Título: dc.titleModeling thermal conductivity, specific Heat, and density of milk: A neural network approach-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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