Detail publikačního výsledku

Sensitivity analysis for parameters of prestressed concrete bridge using neural network ensemble.

PAN, L.; LEHKÝ, D.; NOVÁK, D.; CAO, M.

Originální název

Sensitivity analysis for parameters of prestressed concrete bridge using neural network ensemble.

Anglický název

Sensitivity analysis for parameters of prestressed concrete bridge using neural network ensemble.

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

The paper describes a neural network ensemble-based parameter sensitivity analysis. The proposed method is applied to prestressed concrete bridge. Three dominant parameters were identified for limit state of decompression and six dominant parameters for limit state of crack initiation.

Anglický abstrakt

The paper describes a neural network ensemble-based parameter sensitivity analysis. The proposed method is applied to prestressed concrete bridge. Three dominant parameters were identified for limit state of decompression and six dominant parameters for limit state of crack initiation.

Klíčová slova

Reliability, sensitivity analysis, neural network-ensemble, prestressed concrere bridge

Klíčová slova v angličtině

Reliability, sensitivity analysis, neural network-ensemble, prestressed concrere bridge

Autoři

PAN, L.; LEHKÝ, D.; NOVÁK, D.; CAO, M.

Rok RIV

2019

Vydáno

14.05.2018

Místo

Svratka, Česká republika

ISBN

978-80-86246-88-8

Kniha

Engineering Mechanics 2018

ISSN

1805-8248

Periodikum

Engineering Mechanics

Stát

Česká republika

Strany od

637

Strany do

640

Strany počet

4

Plný text v Digitální knihovně

http://hdl.handle.net/

BibTex

@inproceedings{BUT156409,
  author="Lixia {Pan} and David {Lehký} and Drahomír {Novák} and Maosen {Cao}",
  title="Sensitivity analysis for parameters of prestressed concrete bridge using neural network ensemble.",
  booktitle="Engineering Mechanics 2018",
  year="2018",
  journal="Engineering Mechanics",
  pages="637--640",
  address="Svratka, Česká republika",
  isbn="978-80-86246-88-8",
  issn="1805-8248"
}