Artificial neural networks, which simulate neuronal systems of the brain, are useful methods that have attracted the attention of researchers in many disciplinary areas. They have many advantages over traditional methods in situations where the input-output relationship of the system under study...

An artificial neural forecasting model is developed for air transport passenger analysis. It uses a preprocessing method that decomposes information to reveal relevant features from the data. It is found that neural processing outperforms the traditional econometric approach and offers...

By means of Self-Organizing Maps we cluster fourteen European countries according to the most suitable way to model their agents’ expectations. Using the financial crisis of 2008 as a benchmark, we distinguish between those countries that show a progressive anticipation of the crisis and those...

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourism demand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling...

This paper presents a comparison of various forecasting approaches, using time series analysis, on mean hourly wind speed data. In addition to the traditional linear (ARMA) models and the commonly used feed forward and recurrent neural networks, other approaches are also examined including the...

This paper presents a novel method for the forecasting of mean hourly wind speed data using time series analysis. The initial point for this approach is mainly the fact that none of the forecasting approaches for hourly data, that can be found in the literature, based on time series analysis or...

In this paper, alternative non-parametric forecasting techniques are analysed, with emphasis placed on the difference between the reconstruction and learning approaches. The former is based on Takens’ Theorem, which recovers unknown dynamic properties of a system; it is appropriate in...

To improve ATMs’ cash demand forecasts, this paper advocates the prediction of cash demand for groups of ATMs with similar day-of-the week cash demand patterns. We first clustered ATM centers into ATM clusters having similar day-of-the week withdrawal patterns. To retrieve...

To obtain, over medium term periods, wind speed time series on a site, located in the southern part of the Paris region (France), where long recording are not available, but where nearby meteorological stations provide large series of data, use was made of ANN based models. The performance of...

This paper presents a comparison of two new advanced statistical short-term wind-power forecasting systems developed by two independent research teams. The input variables used in both systems were the same: forecasted meteorological variable values obtained from a numerical weather prediction...