This paper presents and explores the different Earth Observation approaches and their
contribution to the achievement of United Nations Sustainable Development Goals. A review …

This paper presented a review on the capabilities of machine learning algorithms toward
Earth observation data modelling and information extraction. The main purpose was to …

Various numerical methods have been extensively studied and used for reliability analysis
over the past several decades. However, how to understand the effect of numerical …

Assessing the failure probability of complex structure is a difficult task in presence of various
uncertainties. In this paper, a new adaptive approach is developed for reliability analysis by …

Efficient assessment of mechanical system reliability subject to arbitrary probability
distributions and dependent input parameters signifies an important yet challenging task. To …

High-dimensional reliability analysis remains a grand challenge since most of the existing
methods suffer from the curse of dimensionality. This paper introduces a novel high …

Bayesian active learning methods have emerged for structural reliability analysis and shown
more attractive features than existing active learning methods. However, it remains a …

High-dimensional reliability analysis is still an open challenge in structural reliability
community. To address this problem, a new sampling approach, named the good lattice …

This study aims to develop a rotational sparse grid (R-SPGR) method for statistical moment
evaluation and structural reliability analysis with enhanced accuracy and efficiency. The …

To deal with evaluating small failure probabilities, AK–SESC: a novel approach integrating
an active learning Kriging meta-model (AK-MCS) and the SESC, a sequential space …