| Título: | Predicting Grid Resource using SVM and Simulated Annealing Algorithms |
| Autores: |
Han, Yun Liu, Yi |
| Fecha: | 2011-06-03 |
| Publicador: | Innovative systemas design and engineering |
| Fuente: |
 |
| Tipo: |
info:eu-repo/semantics/article Peer-reviewed Article info:eu-repo/semantics/publishedVersion |
| Tema: | No aplica |
| Descripción: | SVM and Simulated Annealing Algorithms were applied to grid resources prediction. In order to build an effective SVR model, the parameters must be selected with attention. Here, a simulated annealing algorithm-based SVR (SA-SVR) model has been developed to determine the optimal parameters of SVR. The performance of the hybrid model, the back-propagation neural network and traditional SVR model whose parameters are provided by trial-and-error procedure have been compared with benchmark data set. Experiments validate that SA-SVR model works better than the other two models. |
| Idioma: | No aplica |