The use of artificial neural networks for mathematical modeling of the effect of composition and production conditions on the properties of PVC floor coverings
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Published:2017
Issue:1
Volume:71
Page:11-18
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ISSN:0367-598X
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Container-title:Chemical Industry
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language:en
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Short-container-title:Hem Ind
Author:
Radovanovic Rajko1,
Jovicic Mirjana2,
Bera Oskar2,
Pavlicevic Jelena2,
Pilic Branka2,
Radicevic Radmila2
Affiliation:
1. ООО JUTEKS RU, Kameškovo, Russian Federation
2. Faculty of Technology, Novi Sad
Abstract
The application of PVC floor coverings is strongly connected with their
end-use properties, which depend on the composition and processing
conditions. It is very difficult to estimate the proper influence of the
production parameters on the characteristics of PVC floor coverings due to
their complex composition and various preparation procedures. The effect of
different processing variables (such as time of bowling, temperature of
bowling and composition of PVC plastisol) on the mechanical properties of PVC
floor coverings was investigated. The influence of different input parameters
on the mechanical properties was successfully determined using an artificial
neural network with an optimized number of hidden neurons. The Garson and
Yoon models were applied to calculate and describe the variable contributions
in the artificial neural networks.
Funder
Ministry of Education, Science and Technological Development of the Republic of Serbia
Publisher
National Library of Serbia
Subject
General Chemical Engineering,General Chemistry