COMPARISON OF RESPONSE SURFACE AND NEURAL NETWORK WITH OTHER METHODS FOR STRUCTURAL RELIABILITY ANALYSIS

By H. Gomes, A. M. Awruch. 2004

286 citations recorded by the source corpus.

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A new approach for solving inverse reliability problems with implicit response functions (2007, methodology): “More recent development of the ANN method may be found in papers by Hurtado and Alvarez [7], Gomes and Awruch [8], Elhewy et al.”
Review and application of Artificial Neural Networks models in reliability analysis of steel structures (2015, methodology): “Gomes and Awruch [26] indicated that the ANN approach is more efficient, however, the examples considered were relatively simple.”
The promise and peril of uncertainty quantification using response surface approximations (2005, background): “Over the past 30 years, response surface approximations have found increasing use in engineering design optimization studies (cf. Simpson et al. 2001) and are becoming increasingly common in engineering UQ studies as well (cf. Gomes and Awruch 2004, Romero et al. 2004, Kaymaz 2005).”
Reliability in composites – a selective review and survey of current development (2012, methodology): “Other methods employing simulation procedures, such as MCM or MC-IS, may have a prohibitive computational cost in large structural systems even if the structural evaluation is accelerated by a vectorized Please cite this article in press as: Chiachio M et al. Reliability in composites – (2011), doi:”