Designing an artificial neural network for forecasting tourism time series

By A. Palmer, J. J. Montaño, A. Sesé. 2006

301 citations recorded by the source corpus.

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Tourism demand modelling and forecasting—A review of recent research (2008, methodology): “Despite the satisfactory forecasting performance, the ANN method does not have a systematic procedure for model building, and a reliable forecasting model is usually achieved through trial-and-error experiments (Kon and Turner, 2005; Palmer et al, 2006).”
Forecasting Accuracy Evaluation of Tourist Arrivals: Evidence from Parametric and Non-Parametric Techniques (2015, unknown): “Other recent studies that focus on biological algorithms include these by Palmer et al. (2006), Hadavandi et al. (2011) and Pai et al. (2014).”
INFORMATION TECHNOLOGY APPLICATIONS IN HOSPITALITY AND TOURISM: A REVIEW OF PUBLICATIONS FROM 2005 TO 2007 (2009, background): “Other researchers have proposed modified neural networks for modeling tourist arrival (Pai & Hong, 2005 ) and time‐series forecasting (Palmer, Montano, & Sese, 2006 ).”
The impact of COVID-19 on tourism sector in India (2020, methodology): “Palmer et al. (2006) described the step-by-step approach to design neural network (NN) for tourism forecasting.”