Abstract :
In this paper, a novel neural network ensemble model, i.e. NNEIPCABag, which combines the feature selection technique, the improved principal component analysis (IPCA), with the Bagging method, is presented. Then the proposed model is employed for time series forecasting with the favor results obtained, which shows that the generalization ability of the proposed model can be superior to that of neural network ensemble only with the Bagging method, .i.e. NNEBag.
Keywords :
neural nets; principal component analysis; time series; Bagging method; feature selection; generalization ability; improved principal component analysis; neural network ensemble model; time series forecasting; Bagging; Boosting; Diversity reception; Economic forecasting; Image coding; Neural networks; Predictive models; Principal component analysis; Training data; Voting; ecnmomic forecasting; feature selection; neural network ensemble;
