Forecasting airline seat show rates with neural networks

Using data supplied by US Airways, a multivariate, externally recurrent neural network is trained using the backpropagation paradigm. Extrapolation of the network to make predictions in the 8 hours and 1 hour booked rate and show rate attained an accuracy of 98%. We have demonstrated that the neural network paradigm can be applied to obtain an optimal management strategy.