CLC number: TU311.2
On-line Access: 2016-12-06
Received: 2015-09-10
Revision Accepted: 2016-03-06
Crosschecked: 2016-11-11
Cited: 0
Clicked: 5821
Cheng-ming Lan , Hui Li, Jun-Yi Peng , Dong-Bai Sun . A structural reliability-based sensitivity analysis method using particles swarm optimization: relative convergence rate[J]. Journal of Zhejiang University Science A, 2016, 17(12): 961-973.
@article{title="A structural reliability-based sensitivity analysis method using particles swarm optimization: relative convergence rate",
author="Cheng-ming Lan , Hui Li, Jun-Yi Peng , Dong-Bai Sun ",
journal="Journal of Zhejiang University Science A",
volume="17",
number="12",
pages="961-973",
year="2016",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1500255"
}
%0 Journal Article
%T A structural reliability-based sensitivity analysis method using particles swarm optimization: relative convergence rate
%A Cheng-ming Lan
%A Hui Li
%A Jun-Yi Peng
%A Dong-Bai Sun
%J Journal of Zhejiang University SCIENCE A
%V 17
%N 12
%P 961-973
%@ 1673-565X
%D 2016
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1500255
TY - JOUR
T1 - A structural reliability-based sensitivity analysis method using particles swarm optimization: relative convergence rate
A1 - Cheng-ming Lan
A1 - Hui Li
A1 - Jun-Yi Peng
A1 - Dong-Bai Sun
J0 - Journal of Zhejiang University Science A
VL - 17
IS - 12
SP - 961
EP - 973
%@ 1673-565X
Y1 - 2016
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1500255
Abstract: This paper proposes a novel reliability-based sensitivity analysis (SA) method, namely relative convergence rate of random variables using particles swarm optimization (). The convergence rate of a random variable during the optimum evolution process reflects the sensitivity of the objective function with respect to the random variables. An optimized group strategy is proposed to consider the fluctuation of the convergence rate of a variable during the optimum process. The coefficient of variation (COV) for candidate particles and the relative convergence rate of a random variable can be calculated using the particles in the optimized group. The smaller the COV for candidate particles, i.e., the larger the relative convergence rate, the more sensitive the objective function with respect to the variable. Three examples are available for the application of this method, and the results indicate that the sensitivity of the reliability index with respect to the variable obtained using the technique and gradient of limit-state function is the same in the quantitative sense.
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