Recommendations for the tuning of rare event probability estimators

被引:7
|
作者
Balesdent, Mathieu [1 ]
Morio, Jerome [2 ]
Marzat, Julien [1 ]
机构
[1] Onera French Aerosp Lab, F-91761 Palaiseau, France
[2] Onera French Aerosp Lab, F-31055 Toulouse, France
关键词
Tuning of simulation parameters; Adaptive importance splitting; Rare event probability estimation; Kriging-based optimization; GLOBAL OPTIMIZATION; SIMULATION; SELECTION; MODELS;
D O I
10.1016/j.ress.2014.09.001
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Being able to accurately estimate rare event probabilities is a challenging issue in order to improve the reliability of complex systems. Several powerful methods such as importance sampling, importance splitting or extreme value theory have been proposed in order to reduce the computational cost and to improve the accuracy of extreme probability estimation. However, the performance of these methods is highly correlated with the choice of tuning parameters, which are very difficult to determine. In order to highlight recommended tunings for such methods, an empirical campaign of automatic tuning on a set of representative test cases is conducted for splitting methods. It allows to provide a reduced set of tuning parameters that may lead to the reliable estimation of rare event probability for various problems. The relevance of the obtained result is assessed on a series of real-world aerospace problems. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:68 / 78
页数:11
相关论文
共 50 条
  • [31] Analysis of exit probability for a trajectory tracking robot in case of a rare event
    Rana, Rohit
    Gaur, Prerna
    Agarwal, Vijyant
    Parthasarathy, Harish
    ROBOTICA, 2022, 40 (04) : 907 - 932
  • [32] Markov chain importance sampling with applications to rare event probability estimation
    Botev, Zdravko I.
    L'Ecuyer, Pierre
    Tuffin, Bruno
    STATISTICS AND COMPUTING, 2013, 23 (02) : 271 - 285
  • [33] The theory of direct probability redistribution and its application to rare event simulation
    Haraszti, Z
    Townsend, JK
    ICC 98 - 1998 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS VOLS 1-3, 1998, : 1443 - 1450
  • [34] An Importance Sampling Method Based on Martingale with Applications to Rare Event Probability
    Qiu, Yue
    Zhou, Hong
    Wu, Yueqin
    2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, : 4041 - 4045
  • [35] Markov chain importance sampling with applications to rare event probability estimation
    Zdravko I. Botev
    Pierre L’Ecuyer
    Bruno Tuffin
    Statistics and Computing, 2013, 23 : 271 - 285
  • [36] Rare Event Analysis for Minimum Hellinger Distance Estimators via Large Deviation Theory
    Vidyashankar, Anand N.
    Collamore, Jeffrey F.
    ENTROPY, 2021, 23 (04)
  • [37] CONTRIBUTIONS TO MAXIMUM PROBABILITY ESTIMATORS
    KUSS, U
    ZEITSCHRIFT FUR WAHRSCHEINLICHKEITSTHEORIE UND VERWANDTE GEBIETE, 1972, 24 (02): : 123 - &
  • [38] EXISTENCE OF MAXIMUM PROBABILITY ESTIMATORS
    WEGNER, H
    ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, 1976, 28 (03) : 343 - 347
  • [39] Boosting conditional probability estimators
    Dan Gutfreund
    Aryeh Kontorovich
    Ran Levy
    Michal Rosen-Zvi
    Annals of Mathematics and Artificial Intelligence, 2017, 79 : 129 - 144
  • [40] Visualizing class probability estimators
    Frank, E
    Hall, M
    KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2003, PROCEEDINGS, 2003, 2838 : 168 - 179