PSI - Issue 23

Petr Opěla et al. / Procedia Structural Integrity 23 (2019) 221 – 226

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Petr O pěla et al. / Structural Integrity Procedia 00 (2019) 000 – 000

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exponents) of these models were approximated with respect to the temperature and strain rate by two different methodologies. The first one is based on the utilizing of a multi-layer feed-forward artificial neural network approach, and the second one is using a universal predictive relationship in combination with the genetic algorithm optimization. The results have showed that both approaches bring a high-accuracy into the flow-curve approximation; however, the ANN approach is slightly better.

Acknowledgements

The article was created thanks to the project No. CZ.02.1.01/0.0/0.0/17_049/0008399 from the EU and CR financial funds provided by the Operational Programme “Research, Development and Education” (Call 02_17_049 “Long - Term Intersectoral Cooperation for ITI”; Managing Authority: Czech Republic – Ministry of Education, Youth and Sports).

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