A review of the application of the simulated annealing algorithm in structural health monitoring (1995-2021)
In recent years, many innovative optimization algorithms have been developed. These
algorithms have been employed to solve structural damage detection problems as an …
algorithms have been employed to solve structural damage detection problems as an …
[HTML][HTML] An unsupervised anomaly detection framework for onboard monitoring of railway track geometrical defects using one-class support vector machine
Track geometry is one of the critical indicators of railway tracks' condition which requires
continuous monitoring and maintenance over time. In this paper, a novel artificial …
continuous monitoring and maintenance over time. In this paper, a novel artificial …
Dynamic wavelet neural network model for damage features extraction and patterns recognition
Monitoring structural damage is essential for preserving and sustaining civil and mechanical
systems' structural service lifecycle. Successful monitoring provides valuable information on …
systems' structural service lifecycle. Successful monitoring provides valuable information on …
Deep learning-based crack identification for steel pipelines by extracting features from 3d shadow modeling
Automatic crack identification for pipeline analysis utilizes three-dimensional (3D) image
technology to improve the accuracy and reliability of crack identification. A new technique …
technology to improve the accuracy and reliability of crack identification. A new technique …
Probabilistic seismic response prediction of three-dimensional structures based on Bayesian convolutional neural network
Seismic response prediction is a challenging problem and is significant in every stage
during a structure's life cycle. Deep neural network has proven to be an efficient tool in the …
during a structure's life cycle. Deep neural network has proven to be an efficient tool in the …
Structural assessment under uncertain parameters via the interval optimization method using the slime mold algorithm
Damage detection of civil and mechanical structures based on measured modal parameters
using model updating schemes has received increasing attention in recent years. In this …
using model updating schemes has received increasing attention in recent years. In this …
Visible particle series search algorithm and its application in structural damage identification
Identifying structural damage is an essential task for ensuring the safety and functionality of
civil, mechanical, and aerospace structures. In this study, the structural damage identification …
civil, mechanical, and aerospace structures. In this study, the structural damage identification …
Coal structure identification based on geophysical logging data: Insights from Wavelet Transform (WT) and Particle Swarm Optimization Support Vector Machine (PSO …
Z Tong, Y Meng, J Zhang, Y Wu, Z Li, D Wang… - International Journal of …, 2024 - Elsevier
Coal structure is closely related to microscopic and macroscopic properties of coal, and its
accurate identification is of great significance to coalbed methane (CBM) reservoir …
accurate identification is of great significance to coalbed methane (CBM) reservoir …
Physics-guided deep neural network for structural damage identification
Z Huang, X Yin, Y Liu - Ocean Engineering, 2022 - Elsevier
The physics-driven method via finite element model and the data-driven methods via
supervised learning is commonly used in the analysis of structural damage identification …
supervised learning is commonly used in the analysis of structural damage identification …
Feature subset selection in structural health monitoring data using an advanced binary slime mould algorithm
R Ghiasi, A Malekjafarian - Journal of Structural Integrity and …, 2023 - Taylor & Francis
Feature Selection (FS) is an important step in data-driven structural health monitoring
approaches. In this paper, an Advanced version of the Binary Slime Mould Algorithm …
approaches. In this paper, an Advanced version of the Binary Slime Mould Algorithm …