Bayesian Networks for Decision-Making and Causal Analysis under Uncertainty in Aviation

Rosa Arnaldo, Victor Fernando Gomez Comendador, Alvaro Rodriguez Sanz, Eduardo Sanchez Ayra, Javier Alberto Perez Castan and Luis Perez Sanz

A chapter in Bayesian Networks - Advances and Novel Applications from IntechOpen

Abstract: Most decisions in aviation regarding systems and operation are currently taken under uncertainty, relaying in limited measurable information, and with little assistance of formal methods and tools to help decision makers to cope with all those uncertainties. This chapter illustrates how Bayesian analysis can constitute a systematic approach for dealing with uncertainties in aviation and air transport. The chapter addresses the three main ways in which Bayesian networks are currently employed for scientific or regulatory decision-making purposes in the aviation industry, depending on the extent to which decision makers rely totally or partially on formal methods. These three alternatives are illustrated with three aviation case studies that reflect research work carried out by the authors.

Keywords: Bayesian networks; prediction; classification; risk; anomaly detection; causal modelling; uncertainty (search for similar items in EconPapers)
JEL-codes: C60 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:159424

DOI: 10.5772/intechopen.79916

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