Please use this identifier to cite or link to this item:
Title: Application of Artificial Neural Networks for Prognostic Modeling of Fire Resistance of Reinforced Concrete Pillars
Authors: Lazarevska, Marijana 
Knezevic, Milos
Cvetkovska, Meri 
Issue Date: Dec-2011
Publisher: Trans Tech Publications
Journal: Applied Mechanics and Materials
Abstract: <jats:p>Artificial neural networks can be used for building prognostic models of various engineering problems. This paper presents an example of how we can predict the time of fire resistance based on the given experimental and numerical results. The analyses concerning the behavior of the reinforced-concrete construction elements during the standard fire, together with the basic theoretical information and detailed problem description, as well as the graphical curves for the fire resistance of the reinforced-concrete pillars, are given in the doctoral theses of Prof. Cvetkovska [3]. Using the concepts of artificial neural networks and the results of the performed numerical analyses as input parameters we made the prediction model for determination of the time of fire resistance of reinforced-concrete pillars. The neural network generated excellent results which will be presented further below in this paper.</jats:p>
DOI: 10.4028/
Appears in Collections:Faculty of Civil Engineering: Journal Articles

Show full item record

Page view(s)

checked on Apr 4, 2020

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.