Chapters authored
Bayesian Networks for Decision-Making and Causal Analysis under Uncertainty in Aviation
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.
Part of the book: Bayesian Networks
Risk Assessment under Uncertainty
System safety assessment (SSA) has become a standard practice in air traffic management (ATM). System safety assessment aims, through a systematic and formal process, to detect, quantify, and diminish the derived risks and to guarantee that critical safety systems achieve the level of safety approved by the regulatory authorities. Verification of compliance with the established safety levels becomes the last but an essential part of the safety assurance process. This chapter provides a Bayesian inference methodology to assess and evaluate the compliance with the established safety levels under the presence of uncertainty in the assessment of systems performances.
Part of the book: Risk Assessment in Air Traffic Management