A hybrid reliability algorithm using PSO-optimized Kriging model and adaptive importance sampling

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 工业控制网络与系统研究室

	A hybrid reliability algorithm using PSO-optimized Kriging model and adaptive importance sampling
	Gong HL(龚海里); Tong C(佟操); Ceng P(曾鹏); Bai HF(白洪飞); Liu YY(刘意杨); Yang RF(杨仁枫)
	2017
会议名称	2017 3rd International Conference on Energy Equipment Science and Engineering, ICEESE 2017
会议日期	December 28-31, 2017
会议地点	Beijing, China
页码	1-9
通讯作者	Tong C(佟操)
中文摘要	This paper aims to reduce the computational cost of reliability analysis. A new hybrid algorithm is proposed based on PSO-optimized Kriging model and adaptive importance sampling method. Firstly, the particle swarm optimization algorithm (PSO) is used to optimize the parameters of Kriging model. A typical function is fitted to validate improvement by comparing results of PSO-optimized Kriging model with those of the original Kriging model. Secondly, a hybrid algorithm for reliability analysis combined optimized Kriging model and adaptive importance sampling is proposed. Two cases from literatures are given to validate the efficiency and correctness. The proposed method is proved to be more efficient due to its application of small number of sample points according to comparison results.
收录类别	EI
产权排序	1
会议录	3rd International Conference on Energy Equipment Science and Engineering, ICEESE 2017
会议录出版者	IOP
会议录出版地	Bristol, UK
语种	英语
ISSN号	1755-1307
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/22031]
专题	沈阳自动化研究所_工业控制网络与系统研究室
作者单位	State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
推荐引用方式 GB/T 7714	Gong HL,Tong C,Ceng P,et al. A hybrid reliability algorithm using PSO-optimized Kriging model and adaptive importance sampling[C]. 见:2017 3rd International Conference on Energy Equipment Science and Engineering, ICEESE 2017. Beijing, China. December 28-31, 2017.