New Type of Aeronautical Risk Assessment: Performance of Kohonen Self-Organizing Maps in Identifying Brazilian Aircraft with Greater Associated Risks

Abstract

Abstract The purpose of this paper is to present a new way of assessing aeronautical risk using a configuration of Kohonen Self-Organizing Maps (SOM) to identify the Brazilian aircraft more likely to be involved in aeronautical accidents and the riskiest Brazilian aircraft. The technique described is classified as predictive for managing aeronautical risks, according to DOC 9859, and can be used both in the context of prevention and investigation of aeronautical accidents/incidents, as well as in the context of the insurance industry. Using this technique, it was possible to identify the 147 Brazilian aircraft with the highest associated probabilities of occurrence of aeronautical accidents, and the 180 with the highest associated risks. Five years after this identification, the respective percentages of aeronautical accidents/incidents were 34% and 27%. The application of this technique can help achieve the objective of the aeronautical community in determining what, where, and when the next aeronautical accidents and/or incidents will occur. Another aspect of the present work is to demonstrate that data collected by the national civil aviation agency in Brazil can be used to implement a predictive methodology for the management of safety in civil aviation.