Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …

To date, data mining (DM) techniques, ie artificial intelligence, machine learning, and
statistical methods have been utilized in a remarkable number of structural health monitoring …

The durability and simplicity of the programming of meta-heuristic algorithms make them
important in the optimization field. This paper presents a novel application for double cracks …

Mode shape-based method has shown its dominance in failure identification of beams.
However, it is a challenge for fault detection in a plate structure. It requires combined …

Laminated composites received great attention in the structural applications due to
innumerable advantages over conventional materials. These structures are subjected to …

Nature-inspired metaheuristic algorithms are gaining popularity with their easy applicability
and ability to avoid local optimum points, and they are spreading to wide application areas …

A simple, yet powerful, new technique based on Artificial Neural Network (ANN) combined
with Particle Swarm Optimization (PSO) for damage quantification in laminated composite …

In this paper, two novel meta-heuristic algorithms are introduced to solve global optimization
problems inspired by the Grey Wolf Optimizer (GWO) algorithm. In the GWO algorithm …

In recent decades, swarm optimization methods have been employed to address various
optimization problems in structural health monitoring (SHM). One of the widely recognized …

Laminated composite structures performance and behavior can be affected by damage that
is not always visible on the surface. The need to monitor the health of these structures has …