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Reconstruction of limit state function based on OELM for reliability computation |
LAI Xiong-ming1, ZHANG Yong1, WANG Cheng2, YAN Lan1, GOU Jin2 |
1. College of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China; 2. College of Computer Science and Technology, Huaqiao University, Xiamen 361021, China |
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Abstract A new efficient method for reconstructing the limit state function was presented based on the optimal extreme learning machine (OELM) for reliability computation aiming at the problem that the limit state function is implicit, nonlinear and computationally time-consuming in reliability estimation. The method determines the important area for reliability. In this area, the advantage of the good generalization for the OELM was used and loop reconstruction of the limit state function was conducted according to certain strategy. The computation of the limit state function was greatly reduced. The important sampling method was used to compute the reliability based on the surrogate reconstructive limit state function. Results show that the method is quite efficient since it can both reduce the computation of the limit state function and ensure the accurate computation for reliability.
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Published: 01 April 2015
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基于OELM重构极限状态函数的可靠度计算方法
针对工程可靠度计算中极限状态函数不解析、非线性、计算量大这一问题,提出基于优化极限学习机高效重构极限状态函数的可靠度计算方法.该方法确定可靠度重要影响区域,在该区域内利用优化极限学习机泛化性能好的优点,按照一定的策略高效循环重构极限状态函数,最大限度地减少极限状态函数的计算次数.基于该重构极限状态函数进行重要抽样可靠性计算.通过实例分析证明,该方法的效率极高,既减少了极限状态函数的计算次数,又能够保证可靠度的计算精度.
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