In order to contribute for enriching studies
in the tourism field, it was intended with this
research paper performing the comparison
between the model based on linear regression
and the model based on artificial neural
networks and analyses of the performance of
those models. Additionally, the usefulness of
the time series that measures the number of
hours of Sunshine should be confirmed. We
used for this purpose the monthly series that
measures the demand for tourism: “Monthly
Nights in Hotels in the Northern Region of
Portugal”, recorded in the period from January
1990 to December 2009.
A linear regression model based on the first
differences was developed producing none
statistical infractions. A previously developed
ANN based model was applied for the new
period of time under comparison. Both models
have the sunshine time series in their entrance.
Both methodologies proved to achieve
similarly good results in getting the seasonality
of the time series, because the correlation
coefficient was at the level of 0.99. Also both
models could predict with high quality the magnitude of the time series because the
mean absolute percentage error was 4.1%
and 3.5% for the linear model and for the ANN
based model, respectively.
