An Neural Network Ensemble approach based on PSO algorithm and LLE for Typhoon Intensity

In this paper, a novel neural network ensemble forecast model is developed where the stepwise regression method are chosen for forecast factors best correlated with the series of typhoon intensity, and the main information is extracted from remaining forecast factors where Locally Linear Embedding (LLE) method is used. Further the problem that network structure determination and network easily into a local solution is considered, a hybrid neural network learning Algorithm is proposed which is based on particle swarm optimization (PSO), Locally Linear Embedding and back propagation algorithm. Finally, the typhoon intensity prediction experiment was conducted in the northwest Pacific Ocean from May to October 2001-2010. The results show that the mean absolute prediction error of neural network ensemble forecast model significantly less than stepwise regression method under the same conditions.