Support vector machine (SVM) is a powerful machine learning technique relying on the
structural risk minimization principle. The applications of SVM in structural reliability analysis …

The present work reviews the implementation of adaptive metamodeling for reliability
analysis with emphasis in four main types of metamodels: response surfaces, polynomial …

Assessing rare event probabilities still suffers from its computational cost despite some
available methods widely accepted by researchers and engineers. For low to moderately …

It is often desirable to evaluate an image based on its quality. For many computer vision
applications, a perceptually meaningful measure is the most relevant for evaluation; …

Various metamodeling approaches eg polynomial response surface method artificial neural
network, Kriging method etc. have been emerged as an effective alternative for solving …

The reliability analysis of complex structures is hindered by the implicit nature of the limit-
state function. For their approximation use has been made of the Response Surface Method …

Wavelet neural network (WNN) has been widely used in the field of civil engineering.
However, WNN can only effectively handle problems of small dimensions as the …

The surrogate model method is widely used in structural reliability analysis to approximate
complex limit state functions. Accurate results can only be obtained when the surrogate …

We propose a simulation-based decision strategy for the proactive maintenance of complex
structures with a particular application to structural health monitoring (SHM). The strategy is …

In order to deal with the issue of huge computational cost very well in direct numerical
simulation, the traditional response surface method (RSM) as a classical regression …