Publication result detail

Inverse analysis based on Small-sample stochastic training of neural network

NOVÁK, D.; LEHKÝ, D.

Original Title

Inverse analysis based on Small-sample stochastic training of neural network

English Title

Inverse analysis based on Small-sample stochastic training of neural network

Type

Paper in proceedings (conference paper)

Original Abstract

The paper suggests a new approach of inverse analysis to obtain parameters of a computational model in order to obtain best agreement witch experimental data. The proposed inverse analysis approach is based on coupling of a computational model and the stochastic training of artificial neural network. The identification parameters play the role of basic random variables with a scatter reflecting the physical range of possible values. A novelty of the approach is the utilization of efficient small-sample simulation method Latin Hypercube Sampling (LHS) used for preparation of training set utilized in stochastic training of neural network. Once the network is trained it represented an approximation consequently utilized in an opposite way: For the given experimental data to provide the best possible set of model parameters.

English abstract

The paper suggests a new approach of inverse analysis to obtain parameters of a computational model in order to obtain best agreement witch experimental data. The proposed inverse analysis approach is based on coupling of a computational model and the stochastic training of artificial neural network. The identification parameters play the role of basic random variables with a scatter reflecting the physical range of possible values. A novelty of the approach is the utilization of efficient small-sample simulation method Latin Hypercube Sampling (LHS) used for preparation of training set utilized in stochastic training of neural network. Once the network is trained it represented an approximation consequently utilized in an opposite way: For the given experimental data to provide the best possible set of model parameters.

Keywords

inverse analysis, Latin Hypercube Sampling, stochastic training of neural network, concrete

Key words in English

inverse analysis, Latin Hypercube Sampling, stochastic training of neural network, concrete

Authors

NOVÁK, D.; LEHKÝ, D.

Released

24.08.2005

Publisher

Stéphane Lecoeuche and Dimitris Tsaptsinos

Location

Lille, France

Book

Novel Applications of Neural Network in Engineering

Pages from

155

Pages to

162

Pages count

8

BibTex

@inproceedings{BUT21414,
  author="Drahomír {Novák} and David {Lehký}",
  title="Inverse analysis based on Small-sample stochastic training of neural network",
  booktitle="Novel Applications of Neural Network in Engineering",
  year="2005",
  pages="155--162",
  publisher="Stéphane Lecoeuche and Dimitris Tsaptsinos",
  address="Lille, France"
}