Reliability Analysis Using Artificial Neural Network Based Adaptive Parameter Differential Evolution Algorithm

N. T. Bui, T. T. Nguyen, V. T. Nguyen, N. L. Tao, H. Hasegawa

研究成果: Conference contribution

抄録

Reliability analysis is one of the methods to consider the safety and stability of an engineering system. It is very important to determine whether a system is safe or not. We need to solve the complex nonlinear and implicit the limit state functions to obtain the reliability index. Traditional reliability analysis methods, First-Order Reliability Method (FORM), Second-Order Reliability Method (SORM), and Monte Carlo simulation (MCS), are not effective and have many limitations. In this paper, at the first step, an artificial neural network was used to model the limit state function. After that, the elite opposition-based learning differential evolution algorithm was selected to solve nonlinear equality constrained optimization problem to find the reliability index and the failure probability of problems in terms of random variables. The proposed method and some reference methods were applied to analyze the test problems in the literature to compare their effectiveness.

本文言語English
ホスト出版物のタイトルProceedings of the 2020 3rd International Conference on Robot Systems and Applications, ICRSA 2020
出版社Association for Computing Machinery
ページ88-93
ページ数6
ISBN(電子版)9781450387644
DOI
出版ステータスPublished - 2020 6 14
外部発表はい
イベント3rd International Conference on Robot Systems and Applications, ICRSA 2020 - Chengdu, China
継続期間: 2020 6 142020 6 16

出版物シリーズ

名前ACM International Conference Proceeding Series

Conference

Conference3rd International Conference on Robot Systems and Applications, ICRSA 2020
国/地域China
CityChengdu
Period20/6/1420/6/16

ASJC Scopus subject areas

  • ソフトウェア
  • 人間とコンピュータの相互作用
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ ネットワークおよび通信

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