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Please use this identifier to cite or link to this item: http://hdl.handle.net/10198/1034

Título: Applying the artificial neural network methodology for forecasting the tourism time series
Autor: Fernandes, Paula O.
Teixeira, João Paulo
Palavras-chave: Artificial neural networks
Time series forecasts
Tourism
Backpropagation
Feedforward
Training
Issue Date: 2008
Citação: Fernandes, Paula O.; Teixeira, João Paulo (2008) - Applying the artificial neural network methodology for forecasting the tourism time series. In 5th International Scientific Conference in ‘Business and Management. Vilnius, Lithuania. ISBN 978-9955-28-267-9
Resumo: This paper aims to develop models and apply them to sensitivity studies in order to predict demand. It provides a deeper understanding of the tourism sector in Northern Portugal and contributes to already existing econometric studies by using the Artificial Neural Networks methodology. This work's focus is on the treatment, analysis, and modelling of time series representing “Monthly Guest Nights in Hotels” in Northern Portugal recorded between January 1987 and December 2005. 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 analysis of the output forecast data of the selected ANN model showed a reasonably close result compared to the target data.
Arbitragem científica: yes
URI: http://hdl.handle.net/10198/1034
Appears in Collections:DEG - Publicações em Proceedings Indexadas ao ISI
DE - Publicações em Proceedings Indexadas ao ISI

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