Publication result detail

Identification of material model parameters using stochastic training of neural network

LEHKÝ, D., NOVÁK, D.

Original Title

Identification of material model parameters using stochastic training of neural network

English Title

Identification of material model parameters using stochastic training of neural network

Type

Paper in proceedings (conference paper)

Original Abstract

A new approach for material model parameters identification is presented. The approach is based on coupling of the stochastic nonlinear analysis and the artificial neural network. Model parameters play the role of random variables. MC type simulation method is then used. The simulation serves for training of neural network.

English abstract

A new approach for material model parameters identification is presented. The approach is based on coupling of the stochastic nonlinear analysis and the artificial neural network. Model parameters play the role of random variables. MC type simulation method is then used. The simulation serves for training of neural network.

Key words in English

Neural network, fracture mechanics, Monte Carlo simulation, identification.

Authors

LEHKÝ, D., NOVÁK, D.

RIV year

2011

Released

16.06.2004

Publisher

Taylor & Francis Group

Location

London

ISBN

90-5809-676-9

Book

5th International PhD Symposium in Civil Engineering

Pages from

535

Pages count

8

BibTex

@inproceedings{BUT12089,
  author="David {Lehký} and Drahomír {Novák}",
  title="Identification of material model parameters using stochastic training of neural network",
  booktitle="5th International PhD Symposium in Civil Engineering",
  year="2004",
  pages="8",
  publisher="Taylor & Francis Group",
  address="London",
  isbn="90-5809-676-9"
}