Utilize este identificador para referenciar este registo: http://hdl.handle.net/10198/9736
Título: Training neural networks by resilient backpropagation algorithm for tourism forecasting
Autor: Fernandes, Paula O.
Teixeira, João Paulo
Ferreira, João
Azevedo, Susana Garrido
Palavras-chave: Neural networks
Time series analysis
Tourism demand forecasting
Resilient backpropagation algorithm
Data: 2013
Editora: Springer
Citação: Fernandes, Paula O.; Teixeira, João Paulo;, Ferreira, João; Azevedo, Susana (2013) - Training neural networks by resilient backpropagation algorithm for tourism forecasting. Management Intelligent Systems, Advances in Intelligent Systems and Computing, Springer. 220, p. 41-49. ISBN 978-3-319-00569-0
Resumo: The main objective of this study is to presents a set of models for tourism destinations competitiveness, using the Artificial Neural Networks (ANN) methodology. The time series of two regions (North and Centre of Portugal) has used to predict the tourism demand. The prediction for two years ahead gives a mean absolute percentage error between 5 and 9 %. Therefore, the ANN model is adequate for modelling and prediction of the reference time series. This model is an important and useful framework for better planning and development of these two regions as they operate in highly competitive markets.
Peer review: yes
URI: http://hdl.handle.net/10198/9736
DOI: 10.1007/978-3-319-00569-0_6
Versão do Editor: http://link.springer.com/chapter/10.1007/978-3-319-00569-0_6#
Aparece nas colecções:DE - Artigos em Revistas Indexados ao ISI/Scopus

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