Inverse Reliability Task: Artificial Neural Networks and Reliability-Based Optimization Approaches - Artificial Intelligence Applications and Innovations (AIAI 2014) Access content directly
Conference Papers Year : 2014

Inverse Reliability Task: Artificial Neural Networks and Reliability-Based Optimization Approaches

David Lehký
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  • PersonId : 992467
Ondřej Slowik
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  • PersonId : 992468
Drahomír Novák
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  • PersonId : 992469

Abstract

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.
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hal-01391333 , version 1 (03-11-2016)

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David Lehký, Ondřej Slowik, Drahomír Novák. Inverse Reliability Task: Artificial Neural Networks and Reliability-Based Optimization Approaches. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. pp.344-353, ⟨10.1007/978-3-662-44654-6_34⟩. ⟨hal-01391333⟩
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