Most of the existing damage detection methods focused on damage along members of the
structure without considering possible damage at its connections. Under the Bayesian …

The fundamental problem of Bayesian model updating is identifying the posterior probability
density function (PDF) of uncertain model parameters. Markov chain Monte Carlo (MCMC) …

Structural damage detection is the kernel technique in deploying structural health
monitoring. The structural damage–detection technique using heuristic algorithms has been …

The paper, through the discussion of an experimental investigation, considers a combined
approach based on artificial neural networks and genetic algorithms for structural damage …

The effect of structural uncertainties or measurement errors on damage detection results
makes the robustness become one of the most important features during identification. Due …

There has been growing interest in applying the artificial neural network (ANN) approach in
structural system identification and health monitoring. The learning process of neural …

Structural damage detection remains as a challenging task in the field of structural health
monitoring (SHM), which has occupied many scientific communities over the last two …

Due to the influence of various uncertain factors, there will inevitably be certain errors
between the prediction of finite-element (FE) model and observed data for a target structure …

Joint damage constitutes a significant form of damage in particular, in the beam-to-column
connection in a steel frame structure. However, it is identified that except only a few neural …

With the rapid development of computation technologies, swarm intelligence–based
algorithms become an innovative technique used for addressing structural damage …