Publication detail

Inverse FEM Analysis I: Stochastic Training of Neural Network

NOVÁK, D. LEHKÝ, D.

Original Title

Inverse FEM Analysis I: Stochastic Training of Neural Network

English Title

Inverse FEM Analysis I: Stochastic Training of Neural Network

Type

conference paper

Language

Czech

Original Abstract

The paper suggests a new approach of inverse analysis to obtain parameters of FEM computational model in order to obtain best agreement witch experimental data. The proposed inverse analysis approach is based on coupling of FEM computational model and the stochastic training of artificial neural network. Identification parameters play the role of basic random variables witch a scatter reflecting the physical range of possible values. Novelty of the approach is the utilization of efficient small-sample simulation method Latin Hypercube Sampling (LHS) used for training of neural network.

English abstract

The paper suggests a new approach of inverse analysis to obtain parameters of FEM computational model in order to obtain best agreement witch experimental data. The proposed inverse analysis approach is based on coupling of FEM computational model and the stochastic training of artificial neural network. Identification parameters play the role of basic random variables witch a scatter reflecting the physical range of possible values. Novelty of the approach is the utilization of efficient small-sample simulation method Latin Hypercube Sampling (LHS) used for training of neural network.

Key words in English

inverse analysis, parameters, Small.sample simulation, Latin Hypercube Sampling, neural network

Authors

NOVÁK, D.; LEHKÝ, D.

RIV year

2005

Released

9. 5. 2005

Location

Svratka, Czech Republic

ISBN

80-85918-93-5

Book

Inženýrská mechanika 2005

Pages from

233

Pages to

244

Pages count

12

BibTex

@inproceedings{BUT21423,
  author="Drahomír {Novák} and David {Lehký}",
  title="Inverse FEM Analysis I: Stochastic Training of Neural Network",
  booktitle="Inženýrská mechanika 2005",
  year="2005",
  pages="12",
  address="Svratka, Czech Republic",
  isbn="80-85918-93-5"
}