| Revista: | Polibits |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000382886 |
| ISSN: | 1870-9044 |
| Autores: | Rodriguez, Nibaldo1 Bravo, Gabriel2 Barba, Lida3 |
| Instituciones: | 1Pontificia Universidad Católica de Valparaíso, Valparaíso. Chile 2Universidad San Sebastián, Concepción. Chile 3Universidad Nacional de Chimborazo, Riobamba, Chimborazo. Ecuador |
| Año: | 2014 |
| Periodo: | Jul-Dic |
| Número: | 50 |
| Paginación: | 49-53 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Aplicado, descriptivo |
| Resumen en inglés | This paper proposes a hybrid multi-step-ahead forecasting model based on two stages to improve pelagic fish-catch time-series modeling. In the first stage, the Fourier power spectrum is used to analyze variations within a time series at multiple periodicities, while the stationary wavelet transform is used to extract a high frequency (HF) component of annual periodicity and a low frequency (LF) component of inter-annual periodicity. In the second stage, both the HF and LF components are the inputs into a single-hidden neural network model to predict the original non-stationary time series. We demonstrate the utility of the proposed forecasting model on monthly anchovy catches time-series of the coastal zone of northern Chile (18°S-24°S) for periods from January 1963 to December 2008. Empirical results obtained for 7-month ahead forecasting showed the effectiveness of the proposed hybrid forecasting strategy |
| Disciplinas: | Ciencias de la computación, Medicina veterinaria y zootecnia |
| Palabras clave: | Procesamiento de datos, Pesca, Peces, Modelos de pronóstico, Captura, Series de tiempo, Manejo pesquero, Redes neuronales, Análisis wavelet |
| Keyword: | Computer science, Veterinary medicine and animal husbandry, Data processing, Fisheries, Forecasting models, Catch, Fish, Time series, Fishery management, Neural networks, Wavelet analysis |
| Texto completo: | Texto completo (Ver HTML) |
