Predicting Airline Passenger Volume

PREDICTING AIRLINE PASSENGER VOLUME By: Kyungdoo Nam, Junsub Yi and Victor R. Prybutok Kyungdoo Nam, Junsub Yi and Victor R. Prybutok Neural networks tend to improve the forecast of airline passenger volume ... compares the forecasting performance of neural networks with those of regression and exponential smoothing... neural networks have an edge over other models particularly where data form a pattern which is difficult to generalize. The classical quantitative techniques available to practitioners and academics for forecasting time series data are diverse, including regression and exponential smoothing. However, these techniques have several specific disadvantages. One, these techniques require assumptions about the underlying function. For example, errors must be independent, and normally distributed with a zero mean and a constant variance. Two, past observations often contain patterns that are difficult to extract, making it difficult to build a model. Three, there is no way to be certain that a given statistical technique will provide the best results. Neural networks tend to overcome these problems. In recent years, neural networks have emerged as an alternative ...