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Article: Modeling, prediction, and analysis of alkyd enamel coating properties via neural computing.
- Article from:
- JCT Research
- Article date:
- April 1, 2006
- Author:
CopyrightCOPYRIGHT 2006 Federation of Societies for Coatings Technology. This material is published under license from the publisher through the Gale Group, Farmington Hills, Michigan. All inquiries regarding rights should be directed to the Gale Group. (Hide copyright information)
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The use of artificial neural networks (ANNs) in the modeling and prediction of alkyd enamel coating properties, as well as in the sensitivity analysis that can be performed between the properties and the different paint components, are described. A feedforward neural network with sigmoidal activation functions was used with a conjugate gradient algorithm to recognize the complex input-output relation between the paint properties and the formula components. We restricted the study to only two properties of alkyd enamel paints: gloss and drying time. A database of five different families of alkyd enamel paints, containing the different components of the formulations as well ...