Inverse reliability task: Artificial neural networks and reliability-based optimization approaches

被引：0
|
作者：
Lehký, David [1 ]
Slowik, Ondřej [1 ]
Novák, Drahomír [1 ]
机构：
[1] Brno University of Technology, Brno, Czech Republic
来源：
IFIP Advances in Information and Communication Technology | 2014年 / 436卷
关键词：
Double-loop - Inverse reliability - Latin hypercube sampling - Reliability based optimization - Uncertainties;
D O I：
10.1007/978-3-662-44654-6_34
中图分类号：
学科分类号：
摘要：
The paper presents two alternative approaches to solve inverse reliability task - to determine the design parameters to achieve desired target reliabilities. The first approach is based on utilization of artificial neural networks and small-sample simulation Latin hypercube sampling. The second approach considers inverse reliability task as reliability-based optimization task using double-loop method and also small-sample simulation. Efficiency of both approaches is presented in numerical example, advantages and disadvantages are discussed. © IFIP International Federation for Information Processing 2014.
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页码：344 / 353
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