Monte Carlo importance sampling optimization for system reliability applications

被引:14
|
作者
Campioni, L [1 ]
Vestrucci, P [1 ]
机构
[1] Univ Bologna, Dipartimento Ingn Energet Nucl Controllo Ambienta, Lab Ingn Nucl, I-40136 Bologna, Italy
关键词
D O I
10.1016/j.anucene.2004.01.004
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
This paper focuses on the reliability analysis of multicomponent systems by the importance sampling technique, and, in particular, it tackles the optimization aspect. A methodology based on the minimization of the variance at the component level is proposed for the class of systems consisting of independent components. The claim is that, by means of such a methodology, the optimal biasing could be achieved without resorting to the typical approach by trials. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1005 / 1025
页数:21
相关论文
共 50 条
  • [41] Offline Deep Importance Sampling for Monte Carlo Path Tracing
    Bako, Steve
    Meyer, Mark
    DeRose, Tony
    Sen, Pradeep
    COMPUTER GRAPHICS FORUM, 2019, 38 (07) : 527 - 542
  • [42] Distributed Detection Fusion via Monte Carlo Importance Sampling
    Rao, Hang
    Shen, Xiaojing
    Zhu, Yunmin
    Pan, Jianxin
    PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016, 2016, : 4830 - 4835
  • [43] COMBINING SEPARABLE MONTE CARLO WITH IMPORTANCE SAMPLING FOR IMPROVED ACCURACY
    Chaudhuri, Anirban
    Haftka, Raphael T.
    PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, VOL 7, 2012, : 927 - 932
  • [44] ADAPTIVE MONTE CARLO SAMPLING GRADIENT METHOD FOR OPTIMIZATION
    Tan, Hui
    2017 WINTER SIMULATION CONFERENCE (WSC), 2017, : 4596 - 4597
  • [45] Separable Monte Carlo combined with importance sampling for variance reduction
    Chaudhuri, A. (anirban.chaudhuri01@gmail.com), 1600, Inderscience Enterprises Ltd., 29, route de Pre-Bois, Case Postale 856, CH-1215 Geneva 15, CH-1215, Switzerland (07):
  • [46] IMPORTANCE SAMPLING IN MONTE-CARLO STUDY OF SEQUENTIAL TESTS
    SIEGMUND, D
    ANNALS OF STATISTICS, 1976, 4 (04): : 673 - 684
  • [47] INTERPRETATION OF CONDITIONAL MONTE-CARLO AS A FORM OF IMPORTANCE SAMPLING
    DUBI, A
    HOROWITZ, YS
    SIAM JOURNAL ON APPLIED MATHEMATICS, 1979, 36 (01) : 115 - 122
  • [48] Advanced Monte Carlo for Acquisition Sampling in Bayesian Optimization
    Garcia-Barcos, Javier
    Martinez-Cantin, Ruben
    ENTROPY, 2025, 27 (01)
  • [49] Design of sparse linear arrays by Monte Carlo importance sampling
    Kay, S
    Saha, S
    IEEE JOURNAL OF OCEANIC ENGINEERING, 2002, 27 (04) : 790 - 799
  • [50] A MONTE-CARLO SAMPLING PLAN FOR ESTIMATING NETWORK RELIABILITY
    FISHMAN, GS
    OPERATIONS RESEARCH, 1986, 34 (04) : 581 - 594