Publicação: Discoloration process modeling by neural network
Carregando...
Data
Orientador
Coorientador
Pós-graduação
Curso de graduação
Título da Revista
ISSN da Revista
Título de Volume
Editor
Elsevier B.V. Sa
Tipo
Artigo
Direito de acesso
Acesso restrito
Resumo
The photo-oxidation of acid orange 52 dye was performed in the presence of H2O2, utilizing UV light, aiming the discoloration process modeling and the process variable influence characterization. The discoloration process was modeled by the use of feedforward neural network. Each sample was characterized by five independent variables (dye concentration, pH, hydrogen peroxide volume, temperature and time of operation) and a dependent variable (absorbance). The neural model has also provided, through Garson Partition coefficients and the Pertubation method, the independent variable influence order determination. The results indicated that the time of operation was the predominant variable and reaction mean temperature was the lesser influent variable. The neural model obtained presented coefficients of correlation on the order 0.98, for sets of trainability, validation and testing, indicating the power of prediction of the model and its character of generalization. (c) 2007 Elsevier B.V. All rights reserved.
Descrição
Palavras-chave
neural modeling, azo dye, UV/H2O2
Idioma
Inglês
Como citar
Chemical Engineering Journal. Lausanne: Elsevier B.V. Sa, v. 140, n. 1-3, p. 71-76, 2008.
