activity
20202023
most citedInference and dynamic decision-making for deteriorating systems with probabilistic dependencies through Bayesian networks and deep reinforcement learning

58 citations · 81 across the 3 of their papers we have counts for

collaborators

4 papers

cs.LG2023

Active learning for structural reliability analysis with multiple limit state functions through variance-enhanced PC-Kriging surrogate models

J. Moran A., P. G. Morato, P. Rigo

Existing active strategies for training surrogate models yield accurate structural reliability estimates by aiming at design space regions in the vicinity of a specified limit stat…

cs.LG2022★ 23 cited

Farm-wide virtual load monitoring for offshore wind structures via Bayesian neural networks

N. Hlaing, Pablo G. Morato, F. d. N. Santos +3

Offshore wind structures are subject to deterioration mechanisms throughout their operational lifetime. Even if the deterioration evolution of structural elements can be estimated…

cs.AI2022★ 58 cited

Inference and dynamic decision-making for deteriorating systems with probabilistic dependencies through Bayesian networks and deep reinforcement learning

Pablo G. Morato, Charalampos P. Andriotis, Konstantinos G. Papakonstantinou +1

In the context of modern environmental and societal concerns, there is an increasing demand for methods able to identify management strategies for civil engineering systems, minimi…

cs.AI2020

Optimal Inspection and Maintenance Planning for Deteriorating Structural Components through Dynamic Bayesian Networks and Markov Decision Processes

P. G. Morato, K. G. Papakonstantinou, C. P. Andriotis +2

Civil and maritime engineering systems, among others, from bridges to offshore platforms and wind turbines, must be efficiently managed as they are exposed to deterioration mechani…