Data mining techniques for improving the reliability of system identification
Advanced Engineering Informatics
Monitoring bridge health using fuzzy case-based reasoning
Advanced Engineering Informatics
Interactive visualisation: A support for system identification
Advanced Engineering Informatics
Hi-index | 0.00 |
This paper introduces methodologies that not only predict the failure load and failure pattern of masonry panels subjected to lateral loadings more accurately, but also closely matches deflection at various locations over the surface of the panel with their experimental results. In this research, Evolutionary Computation is used to model variations in material and geometric properties and also the effects of the boundary types on the behaviour of the panel within linear and non-linear ranges. A cellular automata model is used that utilises a zone similarity concept to map the failure behaviour of a single full scale panel 'the base panel', tested in the laboratory, to estimate variations in material and geometric properties and also boundary effects for any unseen panels.