| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 271.89 KB | Adobe PDF |
Orientador(es)
Resumo(s)
This study seeks to investigate and highlight the usefulness of the Artificial Neural Networks
(ANN) methodology as an alternative to the Box-Jenkins methodology in analysing tourism
demand. To this end, each of the above-mentioned methodologies is centred on the treatment,
analysis and modelling of the tourism time series: “Nights Spent in Hotel Accommodation per
Month”, recorded in the period from January 1987 to December 2006, since this is one of the
variables that best expresses effective demand. The study was undertaken for the North and
Centre regions of Portugal. The results showed that the model produced by using the ANN
methodology presented satisfactory statistical and adjustment qualities, suggesting that it is
suitable for modelling and forecasting the reference series, when compared with the model
produced by using the Box-Jenkins methodology.
Descrição
Palavras-chave
Artificial neural networks ARIMA models Time series forecasting
Contexto Educativo
Citação
Fernandes, Paula O.; Teixeira, João Paulo; Ferreira, João José; Azevedo, Susana Garrido (2008). Modelling tourism demand: a comparative study between artificial neural networks and the Box-Jenkins methodology. Romanian Journal of Economic Forecasting. ISSN 1582-6163. 9:3 p.30-50
Editora
The Institute for Economic Forecasting