Fuzzy weight neural network in the analysis of concrete specimens and R/C column buckling tests
Journal Title: Computer Assisted Methods in Engineering and Science - Year 2011, Vol 18, Issue 4
Abstract
The paper describes the applications of back propagation neural networks with the ability to process input and output variables expressed as fuzzy numbers. The presentation of an algorithm for finding fuzzy neural network weights is followed by three examples of applications of this technique to the problems of implicit modelling of material and structure behaviour. The following problems are considered: prediction of concrete fatigue failure, high performance concrete strength prediction, and prediction of critical axial load for eccentrically loaded reinforced concrete columns.
Authors and Affiliations
Magdalena Jakubek
Keywords
Related Articles
- EP ID EP73985
- DOI -
- Views 162
- Downloads 0
Recent developments in numerical homogenization. (Received in the final form February 11, 2010)
This paper deals with homogenization of non linear fibre-reinforced composites in the coupled thermomechanical field. For this kind of structures, i.e. inclusions randomly dispersed in a matrix, the self consistent metho...
Numerical analysis of radiant warmer
The main objective of this paper is to recognise the heat transfer phenomena between an infant placed in a radiant warmer and the surrounding environment. The influence of the parameters in the computational time during...
Modelling of concrete cover degradation caused by rebar?s corrosion- multicomponent media theory approach. (Received in the final form January 23, 2010)
This paper presents the model based on the theory of multicomponent media that allows modelling of rebar corrosion processes. The presented model extends and consolidates the dissertations that have been described in the...
Solving two-dimensional packing problem using particle swarm optimization
Particle swarm optimization is one of the evolutionary computations which is inspired by social behavior of bird flocking or fish schooling. This research focuses on the application of the particle swarm optimization to...
Recent developments in stabilized Galerkin and collocation meshfree methods
Meshfree methods have been developed based on Galerkin type weak formulation and strong formulation with collocation. Galerkin type formulation in conjunction with the compactly supported approximation functions and poly...