Support vector machine (SVM) is a powerful machine learning technique relying on the
structural risk minimization principle. The applications of SVM in structural reliability analysis …

Structural Reliability analysis (SRA) is one of the prominent fields in civil and mechanical
engineering. However, an accurate SRA in most cases deals with complex and costly …

The prediction of the potential of soil liquefaction induced by the earthquake is a vital task in
construction engineering and geotechnical engineering. To provide a possible solution to …

This paper proposes a uniform design (UD)-based Gaussian process regression (GPR)
method for rapid damage assessment and fragility estimates of bridges. The core idea of the …

Health assessment and monitoring of engineered systems have become one of the fastest
growing multi-disciplinary research areas over the last two decades. One of the largest …

Vectorial modeling concept is proposed in this paper by introducing the matrix theory into
the point modeling concept (surrogate modeling strategy), and an adaptive vectorial …

Soil spatial variability at different supports is vital in the seismic performance assessment of
large-span structural systems, including sea-crossing cable-stayed (SCCS) bridges. This …

Support vector regression (SVR) based metamodel is a powerful mean to alleviate
computational challenge of Monte Carlo simulation (MCS) based reliability analysis of …

This paper presents possible combination of structural responses of concrete dams with
machine learning techniques. Support vector machine (SVM) method is adopted and two …

Building seismic assessment is at the forefront of modern scientific research. Several
researchers have proposed methods for estimating the damage response of buildings …