Soft methods in the prediction and identification analysis of axially compressed R/C columns

Dominika Ziaja; Zenon Waszczyszyn

doi:10.24423/cames.55

Dominika Ziaja Department of Structural Mechanics, Rzeszow University of Technology, Rzeszów
Zenon Waszczyszyn Department of Structural Mechanics, Rzeszow University of Technology, Rzeszów

DOI: http://dx.doi.org/10.24423/cames.55

Abstract

Two problems are presented in the paper concerning axial loading of R/C columns: I) prediction of critical loads, II) identification of concrete strength. The problems were analyzed by two methods: A) Gaussian Processes Method, B) Advanced Back-Propagation Neural Network. The results of the numerical analysis are discussed with respect to numerical efficiency of the applied methods.

Keywords

Gauss Processes Method (GPM), Advanced Back-Propagation Neural Network (ABPNN), Reinforced Concrete (R/C), axial loading, Success Ratio (SR),

References

[1] M. Jakubek. Neural network prediction of load capacity for eccentrically loaded reinforced concrete columns. Computer Assisted Methods in Engineering and Sciences, 19(4): 339–349, 2012.
[2] Ch.M. Bishop. Pattern Recognition and Machine Learning. Springer, 2006.
[3] PEER (Pacific Earthquake Engineering Research Center). University of California, 2004, database.
[4] K. Chudyba. Influence of material and geometrical parameters on load carrying capacity of axially loaded R/C columns [in Polish]. PhD, Cracow UT, 1999, database.
[5] H. Demuth, M. Beale. Neural Network Toolbox for use with MATLAB. User’s Guide version 3. Math Works Inc. Natick MA, 2004.
[6] J.P. Nabney. Netlab – Algorithms for Pattern Recognition. Springer, 2004.
[7] B. Miller. Neurocomputing in selected problems of structural identification and damage detection. Oficyna Wydawnicza Politechniki Rzeszowskiej, 2013.
[8] Z. Waszczyszyn, M. Słoński. Selected problems of artificial neural networks development. In: Z. Waszczyszyn, Ed., Advances of Soft Computing in Engineering, CISM Courses and Lectures, Vol. 512, Springer 2010.