Detail publikace

Sampling strategy for feasible high dimensional Monte Carlo computations

PODROUŽEK, J. BUCHER, C.

Originální název

Sampling strategy for feasible high dimensional Monte Carlo computations

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The proposed sampling strategy enables feasible computation of high dimensional Monte Carlo simulation tasks by minimizing the number of necessary executions. The original aspect of this contribution is a special sampling design that focuses on realizations of stochastic nonstationary processes as input for computationally intensive models in a seismic protection context. Since nonlinear oscillators always respond in a very uncertain manner to random vibrations, the input and output mapping is based on small sample training and image processing. Application example demonstrates the benefits and limitations of the nontraditional approach and implies application analogies from across various disciplines, such as hydrology, water resources, etc.

Klíčová slova

stochastic process, Critical excitation, Reliability analysis, Importance sampling, Identification problem

Autoři

PODROUŽEK, J.; BUCHER, C.

Vydáno

19. 7. 2013

Místo

Brno, Czech Republic

ISBN

978-80-214-4800-1

Kniha

11th International Probabilistic Workshop

Strany od

317

Strany do

323

Strany počet

7

URL

server.stm.fce.vutbr.cz

BibTex

@inproceedings{BUT131106,
  author="Jan {Podroužek} and Christian {Bucher}",
  title="Sampling strategy for feasible high dimensional
Monte Carlo computations",
  booktitle="11th International Probabilistic Workshop",
  year="2013",
  pages="317--323",
  address="Brno, Czech Republic",
  isbn="978-80-214-4800-1",
  url="server.stm.fce.vutbr.cz"
}