Forecasting aviation safety occurrences. (27th February 2022)

• Record Type: Journal Article
• Authors: Flores, Bruno; Rios Insua, David; Alfaro, Cesar; Gomez, Javier
• Is Part Of: Applied stochastic models in business and industry. Volume 38:Number 3(2022)
• Page Start: 545
• Page End: 567
• Publication Date: 2022-02-27
• Subjects: aviation safety -- Bayesian forecasting -- dynamic models -- nonhomogeneous Poisson models; Stochastic analysis -- Periodicals; Stochastic processes -- Periodicals; Business mathematics -- Periodicals; Finance -- Mathematical models -- Periodicals; Industrial management -- Mathematical models -- Periodicals; 338.00151923
• DOI: 10.1002/asmb.2675
• Languages: English
• ISSNs: 1524-1904

Abstract

Abstract: We present a general framework for aviation safety occurrence forecasting. This is a major component of a methodology for aviation safety risk management at national level. It covers novel models as well as novel combinations of earlier models. Having good quality occurrence and severity forecasting models is paramount to properly manage risks, maintain the confidence of its users and preserve the status of aviation as a safe transportation mode. The problem is involved due to the presence of complex effects like seasonality, trends, or stress that impact the rates of various occurrences and the uncertainty about future number of operations.