This study compares the performance of different Artificial Neural Networks models for tourist demand forecasting in a … multiple-output framework. We test the forecasting accuracy of three different types of architectures: a multi-layer perceptron … international tourism demand to Catalonia (Spain) from 2001 to 2012. By means of cointegration analysis we find that growth rates of …

This study attempts to improve the forecasting accuracy of tourism demand by using the existing common trends in …. While most tourism forecasting research focuses on univariate methods, we compare the performance of three different … international tourism demand to Catalonia (Spain). We find that the MIMO approach does not outperform the forecasting accuracy of …

This study attempts to improve the forecasting accuracy of tourism demand by using the existing common trends in …. While most tourism forecasting research focuses on univariate methods, we compare the performance of three different … international tourism demand to Catalonia (Spain). We find that the MIMO approach does not outperform the forecasting accuracy of …

forecasting. We test the forecasting accuracy of three different types of architectures: a multi-layer perceptron, a radial basis …. These results indicate the potential existence of instabilities when using dynamic networks for forecasting purposes. We … also find that for higher memories, the forecasting performance obtained for longer horizons improves, suggesting the …

forecasting. We test the forecasting accuracy of three different types of architectures: a multi-layer perceptron, a radial basis …. These results indicate the potential existence of instabilities when using dynamic networks for forecasting purposes. We … also find that for higher memories, the forecasting performance obtained for longer horizons improves, suggesting the …

This study aims to analyze the effects of data pre-processing on the performance of forecasting based on neural network … demand to Catalonia (Spain) and compare the forecasting accuracy of four processing methods for the input vector of the … networks: levels, growth rates, seasonally adjusted levels and seasonally adjusted growth rates. When comparing the forecasting …

This study aims to analyze the effects of data pre-processing on the performance of forecasting based on neural network … demand to Catalonia (Spain) and compare the forecasting accuracy of four processing methods for the input vector of the … networks: levels, growth rates, seasonally adjusted levels and seasonally adjusted growth rates. When comparing the forecasting …

This study attempts to assess the forecasting accuracy of Support Vector Regression (SVR) with regard to other … Gaussian kernel shows the best forecasting performance. The best predictions are obtained for longer forecast horizons, which … suggest the suitability of machine learning techniques for medium and long term forecasting. …

This study attempts to assess the forecasting accuracy of Support Vector Regression (SVR) with regard to other … Gaussian kernel shows the best forecasting performance. The best predictions are obtained for longer forecast horizons, which … suggest the suitability of machine learning techniques for medium and long term forecasting. …

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more … evaluate the forecasting performance of neural modelling relative to that of time series methods at a regional level … compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official …