Unsupervised learning-based damage assessment of full-scale civil structures under long-term and short-term monitoring
MH Daneshvar, H Sarmadi - Engineering Structures, 2022 - Elsevier
Abstract Machine learning has become an influential and useful tool for many civil
engineering applications, particularly structural health monitoring (SHM). For this reason …
engineering applications, particularly structural health monitoring (SHM). For this reason …
Scale-free networks well done
We bring rigor to the vibrant activity of detecting power laws in empirical degree distributions
in real-world networks. We first provide a rigorous definition of power-law distributions …
in real-world networks. We first provide a rigorous definition of power-law distributions …
Probabilistic data self-clustering based on semi-parametric extreme value theory for structural health monitoring
Clustering is a popular and useful unsupervised learning method with various algorithms for
applying to many engineering problems. However, some practical and technical issues such …
applying to many engineering problems. However, some practical and technical issues such …
Aeva: Black-box backdoor detection using adversarial extreme value analysis
Deep neural networks (DNNs) are proved to be vulnerable against backdoor attacks. A
backdoor is often embedded in the target DNNs through injecting a backdoor trigger into …
backdoor is often embedded in the target DNNs through injecting a backdoor trigger into …
A review of more than one hundred Pareto-tail index estimators
I Fedotenkov - Statistica, 2020 - rivista-statistica.unibo.it
Heavy-tailed distributions are often encountered in economics, finance, biology,
telecommunications, geology, etc. The heaviness of a tail is measured by a tail index …
telecommunications, geology, etc. The heaviness of a tail is measured by a tail index …
Lehmer's mean-of-order-p extreme value index estimation: a simulation study and applications
The main objective of extreme value theory is essentially the estimation of quantities related
to extreme events. One of its main issues has been the estimation of the extreme value index …
to extreme events. One of its main issues has been the estimation of the extreme value index …
Estimation of tail risk based on extreme expectiles
We use tail expectiles to estimate alternative measures to the value at risk and marginal
expected shortfall, which are two instruments of risk protection of utmost importance in …
expected shortfall, which are two instruments of risk protection of utmost importance in …
Unsupervised data normalization for continuous dynamic monitoring by an innovative hybrid feature weighting-selection algorithm and natural nearest neighbor …
H Sarmadi, A Entezami… - Structural Health …, 2023 - journals.sagepub.com
Continuous dynamic monitoring brings an important opportunity to evaluate the health and
integrity of civil structures in a long-term manner. However, high dimensionality and sparsity …
integrity of civil structures in a long-term manner. However, high dimensionality and sparsity …
Threshold selection in extreme value analysis
The main objective of statistics of extremes is the prediction of rare events, and its primary
problem has been the estimation of the extreme value index (EVI). When we are interested …
problem has been the estimation of the extreme value index (EVI). When we are interested …
Fatigue life prediction for AlSi10Mg components produced by selective laser melting
M Tang, PC Pistorius - International journal of fatigue, 2019 - Elsevier
Residual defects in additively manufactured metal parts are known to degrade fatigue
performance. In this work, pores and oxide particles in AlSi10Mg parts produced by selective …
performance. In this work, pores and oxide particles in AlSi10Mg parts produced by selective …