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 paper aims to explore the forecasting accuracy of RON/USD exchange rate structural models with monetary …

forecasting tools for regional employment growth. Because of relevant differences in data availability between the former East and …

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 …

approach,based on the S-estimation method, to construct forecasting models that are less sensitive to data contamination by … accuracy and sign predictability measures. We find that robust models tend to improve the forecasting accuracy of the AR and of …

general, there are five groups of networks used as forecasting tools: 1) Feedforward Networks, like the Multilayer Perceptron … forecasting stock indices and exchange rates. The objective is to assess the performance when applying different types of networks … in relation to MLP. It is shown that the MLP is the best network in forecasting time series. However, it is shown that …