This study seeks to investigate and highlight the usefulness of the Artificial Neural Networks (ANN) methodology as an alternative to the Box-Jenkins methodology in analysing tourism demand. To this end, each of the above-mentioned methodologies is centred on the treatment, analysis and modelling of the tourism time series: “Nights Spent in Hotel Accommodation per Month”, recorded in the period from January 1987 to December 2006, since this is one of the variables that best expresses effective demand. The study was undertaken for the North and Centre regions of Portugal. The results showed that the model produced by using the ANN methodology presented satisfactory statistical and adjustment qualities, suggesting that it is suitable for mode...
Tourism demand is usually characterized by the time series of the “Monthly Number of Guest Nights in...
This paper compares a variety of time-series forecasting methods to predict tourism demand for a cer...
The increasing interest aroused by more advanced forecasting techniques, together with the requireme...
This study seeks to investigate and highlight the usefulness of the Artificial Neural Networks (ANN)...
This study seeks to investigate and highlight the usefulness of the Artificial Neural Networks (ANN...
Several empirical studies in the tourism area have been performed and published during the last dec...
The global tourism industry has witnessed a significant growth in the past few decades. Many researc...
The aim of this research is to quantify the tourism demand using an Artificial Neural Network (ANN)...
This study is aimed to model and forecast the tourism demand for Mozambique for the period from Jan...
This paper aims to develop models and apply them to sensitivity studies in order to predict demand. ...
Abstract In order to contribute for enriching studies in the tourism field, it was intended with ...
This study aimed to model and forecast the tourism demand for Mozambique for the period from Januar...
As it being seen in every sector, demand forecasting in tourism is been conducted with various quali...
The authors have been developing several models based on artificial neural networks, linear regressi...
The modulation of tourism time series was used in this work for forecast purposes. The Tourism Reve...
Tourism demand is usually characterized by the time series of the “Monthly Number of Guest Nights in...
This paper compares a variety of time-series forecasting methods to predict tourism demand for a cer...
The increasing interest aroused by more advanced forecasting techniques, together with the requireme...
This study seeks to investigate and highlight the usefulness of the Artificial Neural Networks (ANN)...
This study seeks to investigate and highlight the usefulness of the Artificial Neural Networks (ANN...
Several empirical studies in the tourism area have been performed and published during the last dec...
The global tourism industry has witnessed a significant growth in the past few decades. Many researc...
The aim of this research is to quantify the tourism demand using an Artificial Neural Network (ANN)...
This study is aimed to model and forecast the tourism demand for Mozambique for the period from Jan...
This paper aims to develop models and apply them to sensitivity studies in order to predict demand. ...
Abstract In order to contribute for enriching studies in the tourism field, it was intended with ...
This study aimed to model and forecast the tourism demand for Mozambique for the period from Januar...
As it being seen in every sector, demand forecasting in tourism is been conducted with various quali...
The authors have been developing several models based on artificial neural networks, linear regressi...
The modulation of tourism time series was used in this work for forecast purposes. The Tourism Reve...
Tourism demand is usually characterized by the time series of the “Monthly Number of Guest Nights in...
This paper compares a variety of time-series forecasting methods to predict tourism demand for a cer...
The increasing interest aroused by more advanced forecasting techniques, together with the requireme...