Fragility assessment approach of deepwater drilling risers subject to harsh environments using Bayesian regularization artificial neural network

Research article (Ocean Engineering, 2021) · cited 13× · AI/ML
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Fragility assessment approach of deepwater drilling risers subject to harsh environments using Bayesian regularization artificial neural network

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Fragility assessment approach of deepwater drilling risers subject to harsh environments using Bayesian regularization artificial neural network is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Fragility assessment approach of deepwater drilling risers subject to harsh environments using Bayesian regularization artificial neural network. Retrieved May 24, 2026, from https://4ort.xyz/entity/fragility-assessment-approach-of-deepwater-drilling-risers-subject-to-harsh-environments-using-bayesian-regularization-a
MLA “Fragility assessment approach of deepwater drilling risers subject to harsh environments using Bayesian regularization artificial neural network.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/fragility-assessment-approach-of-deepwater-drilling-risers-subject-to-harsh-environments-using-bayesian-regularization-a.
BibTeX @misc{4ortxyz_fragility-assessment-approach-of-deepwater-drilling-risers-subject-to-harsh-environments-using-bayesian-regularization-a_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Fragility assessment approach of deepwater drilling risers subject to harsh environments using Bayesian regularization artificial neural network}}, year = {2026}, url = {https://4ort.xyz/entity/fragility-assessment-approach-of-deepwater-drilling-risers-subject-to-harsh-environments-using-bayesian-regularization-a}, note = {Accessed: 2026-05-24}}
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