[an error occurred while processing this directive]
   
 
���¿��ټ��� �߼�����
   ��ҳ  �ڿ�����  ��ί��  Ͷ��ָ��  �ڿ�����  ��������  �� �� ��  ��ϵ����
�������պ����ѧѧ�� 2011, Vol. 37 Issue (6) :705-710,716    DOI:
���� ����Ŀ¼ | ����Ŀ¼ | ������� | �߼����� << | >>
�ɿ��������ȷ�����һ��ƫ�����ؿ��޷���
���1, ����1*
1. �������պ����ѧ �ɿ�����ϵͳ����ѧԺ, ���� 100191;
2. ������������ѧ���˷�У ������ɿ�������, ������ 20742
Biased Monte Carlo method for reliability sensitivity analysis
Li Jinghui1, Kang Rui1, Ali Mosleh2*
1. School of Reliability and Systems Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
2. Center for Risk and Reliability, University of Maryland, College Park, MD 20742, USA

ժҪ
�����
�������
Download: PDF (1KB)   HTML 1KB   Export: BibTeX or EndNote (RIS)      Supporting Info
ժҪ ���ݿɿ��������ȷ�����������ص�,ѡ����Ȼ�ȷ�����Ϊ�����ĵ���/�ݶȹ��Ʒ���.���㾭��ɿ���ϵͳ�ͻ���Ԫ�������ؿ��޷���,�Ƶ���ԭʼ���ؿ��޷��滷���µ���Ȼ�ȵ������Ʒ���.Ϊ���ٷ���,��һ�������һ��ƫ�м���,�ü�����ϵͳ�ṹ�����Ļ����϶���һ��Ӧ����Ҫ��������ƫ������,��ͨ����С���ù������ķ������������ƫ�в���ֵ.�ù�����ӵ�е�һ����Ҫ�������䷽���Ż�������Էֽ⵽����Ԫ���IJ���Ͻ���,�Ӷ������˸�ά�Ż�������.ͨ��һ���ɽ������ļ�ʵ����֤����Ȼ�ȵ������Ʒ���Ӧ���ڿɿ��������ȷ�������Ч��,�Լ��������ƫ�м��ɶ��ڽ��͵������Ʒ������Ч��.���������ǵ�ʵ��ϵͳ,�����ƫ�����ؿ��޷����Ը�������Ȥ�����������˺ܺõĹ���,��ԭʼ���ؿ��޷������,�����������ķ��������������6��������.
Service
�ѱ����Ƽ�������
�����ҵ����
�������ù�����
Email Alert
RSS
�����������
�ؼ����� �ɿ���   �����ȷ���   ���ؿ��޷���   ��������   �ݶȹ���   ��Ȼ��   ��Ҫ����     
Abstract�� The likelihood ratio (LR) method was chosen as the basic derivative/gradient estimation method for reliability sensitivity analysis. The implementation of the LR method in crude component-based Monte Carlo (MC) and especially in the setting of classical reliability was first derived. To speed up the simulation, a biasing technique was then developed, which defines an unbiased importance sampling estimator based on system structure functions, and identifies the optimal set of biasing parameters via minimizing the variance of this estimator. One important advantage of this estimator is that, the task of minimizing its variance can be achieved by optimizing at the component level, thus avoiding the difficulty of high dimensional optimizations. A simple example with analytical solution available was studied to test the effectiveness of the LR method for reliability sensitivity analysis, and also the effectiveness of the proposed biasing technique for reducing the variance of LR derivative estimators. The results show that, the proposed biased MC method produced accurate estimates for all the quantities, and achieved at least six orders of magnitude of variance reduction for all of them, compared to crude MC��
Keywords�� reliability   sensitivity analysis   Monte Carlo methods   derivative estimation   gradient estimation   likelihood ratio   importance sampling     
Received 2010-12-21;
About author: ���(1984-),��,����¦����,��ʿ��,sophialjh@dse.buaa.edu.cn.
���ñ���:   
���, ����.�ɿ��������ȷ�����һ��ƫ�����ؿ��޷���[J]  �������պ����ѧѧ��, 2011,V37(6): 705-710,716
Li Jinghui, Kang Rui, Ali Mosleh.Biased Monte Carlo method for reliability sensitivity analysis[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2011,V37(6): 705-710,716
���ӱ���:  
http://bhxb.buaa.edu.cn//CN/     ��     http://bhxb.buaa.edu.cn//CN/Y2011/V37/I6/705
Copyright 2010 by �������պ����ѧѧ��