Bayesian Networks to Quantify Transition Rates in Degradation Modeling ; Bayesian Networks to Quantify Transition Rates in Degradation Modeling: Application to a Set of Steel Bridges in The Netherlands
International audience ; Bridge lifetime pose an important challenge in terms of maintenance for decision makers or asset managers. In this regard Markov chains have been used successfully in practice as models for bridge deterioration. However, one limitation of Markov chains can be the assessment of the transition probabilities. In this paper, we propose an approach based on Bayesian networks (BNs) to quantify the transition probabilities of the system state. One of the advantages of doing so is that the BN may be quantified through physical variables linked to the underlying degradation pro... Mehr ...
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Dokumenttyp: | conferenceObject |
Erscheinungsdatum: | 2015 |
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HAL CCSD
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Schlagwörter: | [SPI.GCIV]Engineering Sciences [physics]/Civil Engineering / [SPI.GCIV.RISQ]Engineering Sciences [physics]/Civil Engineering/Risques / [SPI.GCIV.STRUCT]Engineering Sciences [physics]/Civil Engineering/Structures / [MATH.MATH-PR]Mathematics [math]/Probability [math.PR] |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-29174150 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://hal.science/hal-01517154 |