Detail publikace

Sensitivity analysis of prestressed concrete girders based on artificial neural network surrogate model.

Originální název

Sensitivity analysis of prestressed concrete girders based on artificial neural network surrogate model.

Anglický název

Sensitivity analysis of prestressed concrete girders based on artificial neural network surrogate model.

Jazyk

en

Originální abstrakt

The paper describes a neural network ensemble-based parameter sensitivity analysis, which is compared with selected sensitivity analysis techniques usually utilized in stochastic structural modeling. The accuracy, stability and efficiency of the mentioned sensitivity analysis techniques are compared on example of prestressed concrete girder.

Anglický abstrakt

The paper describes a neural network ensemble-based parameter sensitivity analysis, which is compared with selected sensitivity analysis techniques usually utilized in stochastic structural modeling. The accuracy, stability and efficiency of the mentioned sensitivity analysis techniques are compared on example of prestressed concrete girder.

BibTex


@inproceedings{BUT156408,
  author="Lixia {Pan} and David {Lehký} and Drahomír {Novák} and Ondřej {Slowik}",
  title="Sensitivity analysis of prestressed concrete girders based on artificial neural network surrogate model.",
  annote="The paper describes a neural network ensemble-based parameter sensitivity analysis, which is compared with selected sensitivity analysis techniques usually utilized in stochastic structural modeling. The accuracy, stability and efficiency of the mentioned sensitivity analysis techniques are compared on example of prestressed concrete girder.",
  booktitle="16th International Probabilistic Workshop",
  chapter="156408",
  doi="10.1002/best.201800059",
  howpublished="online",
  number="S2s",
  year="2018",
  month="september",
  pages="1--5",
  type="conference paper"
}