This review identifies current machine-learning algorithms implemented in building
structural health monitoring systems and their success in determining the level of damage in …

The goal of this paper is to present a review of multi-objective optimization (MOO)
techniques used in the damage assessment of composite laminates, with regard to damage …

Recent advances in machine learning have enabled powerful strategies for autonomous
data-driven damage detection and identification in structural systems. This work proposes a …

With the help of pervasive computing, human living has changed into a smarter way using
the developments in IoMT, telecommunication technologies, and wearable sensors for …

This study presents a comprehensive study on the potential and efficacy of decomposition-
based multi-objective symbiotic organism search (MOSOS/D) algorithm for truss structure …

In order to solve challenging engineering problems, the state‐of‐the‐art in multi‐objective
optimization shows a trend toward using meta‐heuristics and a posteriori decision‐making …

The article focuses on the presentation and comparison of selected heuristic algorithms for
solving the inverse problem for the anomalous diffusion model. Considered mathematical …

This study performs a substantial statistical analysis on the effects of damage characteristics,
such as position and severity, on a specific damage metric composed of coefficients …

This paper proposes a multi-document summarization model using an optimization
algorithm named CAVIAR Sun Flower Optimization (CAV-SFO). In this method, two …

Piezoelectric impedance sensing is promising for highly accurate damage identification
because of its high-frequency active interrogative nature and simplicity in data acquisition …