Abstract
It can be said of science in general and paper technology in particular, that using computers and advanced software is increasingly essential. Papercoating is a complex and multivariable process that is, in many cases, nonlinear. It is often necessary to find relationships between the variables that affect the properties of coated paper. This is being achieved through the neural networks that are applied to establish underlying relations contained in the data. Models to estimate brightness, opacity, gloss and print gloss of coated paper are developed using a radial basis function neural network.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
