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Publicação
Prediction tourism demand using artificial neural networks
Orientador(es)
Resumo(s)
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.
Descrição
Palavras-chave
Time series Tourism demand Artificial neural networks Prediction
Contexto Educativo
Citação
Fernandes, Paula O.; Teixeira, João Paulo (2008). Prediction tourism demand using artificial neural networks. In International Conference in European Union’s History, Culture and Citizenship. Pitesti, Romania. ISBN 978-973-690-764-7
Editora
University of Pitesti