Forecasting aviation accidents with the aid of probabilistic models


A probabilistic model for forecasting aviation accidents on the basis of historical data is under consideration. Discrete-states continuous-time Markov processes are applied to obtain probabilistic distributions of accidents for given time periods. A numerical algorithm for identifying model parameters is presented. The results obtained can be used by airlines to plan their activities.