Publicação
Forecasting of a non-seasonal tourism time series with ANN
| Resumo: | The paper present and discusses several alternative architectures of Artificial Neural Network models used to predict the time series of tourism demand for Cape Verde. This time series is particularly difficult to predict due to its non-seasonal characteristic usual in a similar time series for European Tourism destinations. The time index used as input and other input parameters variations improved the performance of the prediction over the test set to a relative error of 7.3% and a Pearson correlation coefficient of 0.92. |
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| Autores principais: | Teixeira, João Paulo |
| Outros Autores: | Fernandes, Paula Odete |
| Assunto: | ANN Forecast Non-seasonal time series Tourism Cape Verde |
| Ano: | 2014 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| Resumo: | The paper present and discusses several alternative architectures of Artificial Neural Network models used to predict the time series of tourism demand for Cape Verde. This time series is particularly difficult to predict due to its non-seasonal characteristic usual in a similar time series for European Tourism destinations. The time index used as input and other input parameters variations improved the performance of the prediction over the test set to a relative error of 7.3% and a Pearson correlation coefficient of 0.92. |
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