Prediction tourism demand using artificial neural networks

The aim of this research is to quantify the tourism demand using an Artificial Neural Network (ANN) model. The methodology was focused in the treatment, analysis and modulation of the tourism time series: “Monthly Guest Nights in Hotels” in Northern Portugal recorded between January 1987 and December 2006, since it is one of the variables that better explain the effective tourism demand. The model used 4 neurons in the hidden layer with the logistic activation function and was trained using the Resilient Backpropagation algorithm. Each time series forecast depended on 12 preceding values. The developed model yielded acceptable goodness of fit and statistical properties and therefore it is adequate for the modulation and prediction of the reference time series.

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