Application of Artificial Neural Networks for Prognostic Modeling of Fire Resistance of Reinforced Concrete Pillars
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.
Artificial neural networks prognostic model fire resistance reinforced-concrete pillars
Lazarevska Marijana Knezevic Milos Cvetkovska Meri
Blvd. Partizanski odredi 24, Skopje, Macedonia Cetinjski put b.b, Podgorica, Montenegro
国际会议
大连
英文
856-861
2011-10-19（万方平台首次上网日期，不代表论文的发表时间）