A New Strategy of SVR Modeling Based on Clustering Algorithm

Aiming at sovling the difficulty of modeling dynamic system with a single model by SVR(support vector regression),a new learning strategy is proposed.Firstly,the clustering algorithm combining SOM(self-organizing map) neural network with k-means algorithm is applied to cluster the original sample set dynamically.Then,the final model of each clustering sample set is established by the optimal weighted combination of different kernel functions of SVR models.The experimental result shows that the proposed learning strategy has much better generalization ability and prediction precision than the single SVR model.