Reliability modeling and prediction of passive controlled structures through Random Forest

Reliability prediction plays a significant role in risk assessment of engineering structures. Mathematically, the prediction task can be seen as a classification (regression) procedure. In this aspect, machine learning methods have recently shown their superior performance over others in various res...

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Bibliographic Details
Published inMATEC Web of Conferences Vol. 241; p. 1023
Main Authors You, Weizhen, Alexandre, Saidi, Ichchou, Mohamed, Abdel, Zine, Zhong, Xiaopin
Format Journal Article Conference Proceeding
LanguageEnglish
Published Les Ulis EDP Sciences 01.01.2018
EDP sciences
Subjects
Acoustics
Analysis of PDEs
Engineering Sciences
Functional Analysis
Machine learning
Materials
Mathematics
Model accuracy
Numerical Analysis
Passive control
Performance evaluation
Performance prediction
Reactive fluid environment
Reliability analysis
Reliability engineering
Risk assessment
Robustness (mathematics)
Structural reliability
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Summary:Reliability prediction plays a significant role in risk assessment of engineering structures. Mathematically, the prediction task can be seen as a classification (regression) procedure. In this aspect, machine learning methods have recently shown their superior performance over others in various research domains. Random forest (RF) is distinguished for its robustness and high accuracy in modeling and prediction work. However, its application in the area of structural reliability has not been widely explored. This study aims to explore the feasibility of RF as well as examine its performance in modeling and prediction of structure reliability in passive control mode. A numerical example is introduced in the simulation part to evaluate performance of the proposed method in different perspectives.
ISSN:2261-236X
2274-7214
2261-236X
DOI:10.1051/matecconf/201824101023