Fangqiong Luo

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Stock market predictions comprise challenging applications of modern time series forecasting and are essential to the success of many businesses and financial institutions. In this paper, a novel nonlinear combination model is presented for stock market forecasting, which based on Support Vector Machine (SVM) regression combining the linear regression of(More)
First of all, Learning matrix of Neural Network get by Projection Pursuit and Particle Swarm Optimization algorithm which Particle Swarm Optimization algorithm optimize projection index from high dimensionality to a lower dimensional subspace, and then many individual neural networks are generated by Samples Reconstruction based on negative correlation(More)
Accurate forecasting of rainfall has been one of the most important issues in hydrological research. Due to rainfall forecasting involves a rather complex nonlinear data pattern; there are lots of novel forecasting approaches to improve the forecasting accuracy. This paper proposes a Projection Pursuit Regression and Neural Networks (PPR--NNs) model for(More)
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