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Data pre-processing for neural network-based forecasting: does it really matter?

Autor
Claveria, O.; Monte, E.; Torra Porras, Salvador
Tipus d'activitat
Article en revista
Revista
Technological and economic development of economy (Spausdinta)
Data de publicació
2015-11-04
Volum
23
Número
5
Pàgina inicial
709
Pàgina final
725
DOI
https://doi.org/10.3846/20294913.2015.1070772 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/81362 Obrir en finestra nova
URL
http://www.tandfonline.com/doi/abs/10.3846/20294913.2015.1070772 Obrir en finestra nova
Resum
This study aims to analyze the effects of data pre-processing on the forecasting performance of neural network models. We use three different Artificial Neural Networks techniques to predict tourist demand: multi-layer perceptron, radial basis function and the Elman neural networks. The structure of the networks is based on a multiple-input multiple-output (MIMO) approach. We use official statistical data of inbound international tourism demand to Catalonia (Spain) and compare the forecasting ac...
Citació
Claveria, O., Monte, E., Torra Porras, S. Data pre-processing for neural network-based forecasting: does it really matter?. "Technological and Economic Development of Economy", 04 Novembre 2015.
Paraules clau
Artificial neural networks, Detrending, Elman, Forecasting, Multilayer perceptron, Multiple-input multiple-output (MIMO), Radial basis function, Seasonality, Tourism demand
Grup de recerca
IDEAI-UPC Intelligent Data Science and Artificial Intelligence
TALP - Centre de Tecnologies i Aplicacions del Llenguatge i la Parla
VEU - Grup de Tractament de la Parla

Participants