Detail publikace

ANN inverse analysis based on stochastic small-sample training set simulation

NOVÁK, D. LEHKÝ, D.

Originální název

ANN inverse analysis based on stochastic small-sample training set simulation

Typ

článek v časopise - ostatní, Jost

Jazyk

angličtina

Originální abstrakt

A new approach of inverse analysis is proposed to obtain parameters of a computational model in order to achieve the best agreement with experimental data. The inverse analysis is based on the coupling of a stochastic simulation and an artificial neural network (ANN). The identification parameters play the role of basic random variables with a scater reflecting the physical range of potential values. A nonovelty of the approach is the utilization of the efficient small-sample simulation method LatinHypercube Sampling (LHS) used for the stochastic preparation of the training set utilized in training the artificial neural network.

Klíčová slova

Inverse analysis, identification, Latin hypercube sampling, artifical neural network, concrete

Autoři

NOVÁK, D.; LEHKÝ, D.

Rok RIV

2006

Vydáno

19. 5. 2006

Nakladatel

Elsevier

Místo

Velká Británie

ISSN

0952-1976

Periodikum

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Ročník

19

Číslo

5

Stát

Spojené království Velké Británie a Severního Irska

Strany od

731

Strany do

740

Strany počet

10

BibTex

@article{BUT44443,
  author="Drahomír {Novák} and David {Lehký}",
  title="ANN inverse analysis based on stochastic small-sample training set simulation",
  journal="ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE",
  year="2006",
  volume="19",
  number="5",
  pages="731--740",
  issn="0952-1976"
}