Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/31000
Título: | Global and decomposition evolutionary support vector machine approaches for time series forecasting |
Autor(es): | Cortez, Paulo Donate, Juan Peralta |
Palavras-chave: | Estimation distribution algorithm Support vector machines Time series Decomposition forecasting Model selection |
Data: | Out-2014 |
Editora: | Springer Verlag |
Revista: | Neural Computing and Applications |
Resumo(s): | Multi-step ahead Time Series Forecasting (TSF) is a key tool for support- ing tactical decisions (e.g., planning resources). Recently, the support vector machine emerged as a natural solution for TSF due to its nonlinear learning capabilities. This paper presents two novel Evolutionary Support Vector Machine (ESVM) methods for multi-step TSF. Both methods are based on an Estimation Distribution Algorithm (EDA) search engine that automatically performs a simultaneous variable (number of inputs) and model (hyperparameters) selection. The Global ESVM (GESVM) uses all past patterns to fit the support vector machine, while the Decomposition ESVM (DESVM) separates the series into trended and stationary effects, using a distinct ESVM to forecast each effect and then summing both predictions into a sin- gle response. Several experiments were held, using six time series. The proposed approaches were analyzed under two criteria and compared against a recent Evolu- tionary Artificial Neural Network (EANN) and two classical forecasting methods, Holt-Winters and ARIMA. Overall, the DESVM and GESVM obtained competitive and high quality results. Furthermore, both ESVM approaches consume much less computational effort when compared with EANN. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/31000 |
DOI: | 10.1007/s00521-014-1593-1 |
ISSN: | 0941-0643 |
Versão da editora: | The original publication is available at: http://link.springer.com/article/10.1007/s00521-014-1593-1 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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nca-esvm3.pdf | Documento principal | 198,64 kB | Adobe PDF | Ver/Abrir |