Uncertainty Handling in Structural Damage Detection via Non-Probabilistic Meta-Models and Interval Mathematics, a Data-Analytics Approach

Review of Vibration-Based Structural Health Monitoring Using Deep Learning

(2020) Gyungmin Toh et al.   Applied Sciences-Basel

Application of wavelet transform in structural health monitoring

(2020) Yashodhya Kankanamge et al.   Earthquake Engineering and Engineering Vibration

Applications of machine learning to machine fault diagnosis: A review and roadmap

(2020) Yaguo Lei et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Data-Driven Structural Health Monitoring and Damage Detection through Deep Learning: State-of-the-Art Review

(2020) Mohsen Azimi et al.   SENSORS

An efficient two-stage approach for structural damage detection using meta-heuristic algorithms and group method of data handling surrogate model

(2020) Hamed Fathnejat et al.   Frontiers of Structural and Civil Engineering

A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications

(2020) Onur Avci et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A nonprobabilistic structural damage identification approach based on orthogonal polynomial expansion and interval mathematics

(2019) Jiang Mo et al.   Structural Control & Health Monitoring

Structural health monitoring using extremely compressed data through deep learning

(2019) Mohsen Azimi et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Non-probabilistic method to consider uncertainties in frequency response function for vibration-based damage detection using Artificial Neural Network

(2019) Khairul H. Padil et al.   JOURNAL OF SOUND AND VIBRATION

Emerging artificial intelligence methods in structural engineering

(2018) Hadi Salehi et al.   ENGINEERING STRUCTURES

Non-probabilistic wavelet method to consider uncertainties in structural damage detection

(2018) Muyideen Abdulkareem et al.   JOURNAL OF SOUND AND VIBRATION

A Bayesian Learning Method for Structural Damage Assessment of Phase I IASC-ASCE Benchmark Problem

(2018) Chang Kook Oh et al.   KSCE Journal of Civil Engineering

Predicting the variability of natural frequencies and its causes by Second-Order Blind Identification

(2018) Carlo Rainieri et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

The use of a non-probabilistic artificial neural network to consider uncertainties in vibration-based-damage detection

(2017) Khairul H. Padil et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

The need for introduction of non-probabilistic interval conceptions into structural analysis and design

(2016) ZhiPing Qiu et al.   Science China-Physics Mechanics & Astronomy

A machine-learning approach for structural damage detection using least square support vector machine based on a new combinational kernel function

(2016) Ramin Ghiasi et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Dealing with uncertainty in model updating for damage assessment: A review

(2015) Ellen Simoen et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

The application of a damage detection method using Artificial Neural Network and train-induced vibrations on a simplified railway bridge model

(2013) Jiangpeng Shu et al.   ENGINEERING STRUCTURES

Structural damage measure index based on non-probabilistic reliability model

(2013) Xiaojun Wang et al.   JOURNAL OF SOUND AND VIBRATION

Seismic reliability assessment of RC structures including soil–structure interaction using wavelet weighted least squares support vector machine

(2012) Mohsen Khatibinia et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Optimum shape design of arch dams for earthquake loading using a fuzzy inference system and wavelet neural networks

(2009) S. M. Seyedpoor et al.   ENGINEERING OPTIMIZATION