Structural damage assessment is crucial for structural health monitoring to evaluate the
safety and residual service life of the structure. To solve the structural damage detection …

The aim of this study is to develop a hybrid Artificial Neural Network-Particle Swarm
Optimization (ANN-PSO) model for improving shear strength prediction of reinforced …

This paper presents an approach of inverse damage detection and localization based on
model reduction. The problem is formulated as an inverse problem where an optimization …

Structural health monitoring is crucial for the timely damage diagnosis of civil infrastructure.
This paper explores the damage detection method based on the ant colony algorithm (ACO) …

The aim of this study is to develop an efficient hybrid machine learning (ML) model, which
combines the genetic algorithm (GA) and artificial neural network (ANN) for rapidly …

Simultaneous identification of multiple cracks is an unresolved issue in the structural health
monitoring field. To address this issue, a new method is proposed for identifying multiple …

Damage detection in structures using the change of modal parameters (modal shapes and
natural frequencies) has achieved satisfactory results. However, as modal shapes and …

Use of swarm intelligence has proliferated over previous couple of years for damage
assessment in large and complex structures using vibration data. Available literatures shows …

Hoje em dia, a gestão de um vasto acervo de estruturas complexas e infraestruturas, que se
encontram próximo ou para lá do seu fim de vida útil, constitui um importante desafio para …

The assessment of structures after an earthquake is a critical aspect of ensuring the safety
and reliability of structural engineering. This study presents an evaluation of the efficacy of …