Journal
PROBABILISTIC ENGINEERING MECHANICS
Volume 36, Issue -, Pages 63-71Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.probengmech.2014.03.005
Keywords
Non-Gaussian process; Non-stationary process; Simulation; Identification; Kernel estimator; Principal component analysis
Funding
- National French ANR Project MODNAT
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A method for constructing probabilistic models of non-stationary time dependent natural hazards is proposed. It is based on the use of Karhunen-Loeve expansion and of a kernel estimator for the distribution of the multivariate random variables appearing in the expansion. The terms of the expansion and the distribution are identified from available measures. The approach is assessed through an academic example and is then applied to seismic ground motion modelling based on recorded data. (C) 2014 Elsevier Ltd. All rights reserved.
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