Data-driven identification of critical components in complex technical infrastructures using Bayesian additive regression trees

Xuefei Lu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Complex technical infrastructures are systems-of-systems characterized by hierarchical structures, made by thousands of interconnected components performing different functions associated to various domains. Given the difficulty of deriving their functional logic using traditional risk and reliability analysis methods, we address the problem of critical component identification from an innovative perspective, which exploits the large amount of available monitored data of operation. Specifically, we develop a data-driven framework of analysis which employs Bayesian additive regression trees and validate it on a synthetic case study, which mimics the complexity of a complex technical infrastructure.
Original languageEnglish
Title of host publicationProceedings of the 29th European Safety and Reliability Conference (ESREL)
EditorsMichael Beer, Enrico Zio
PublisherResearch Publishing
ISBN (Electronic)9789811127243
DOIs
Publication statusPublished - 30 Sept 2019

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