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PSO is an overall stochastic optimization algorithm based on the selection of the feature set and optimization of kernel function parameters, which has great impact on the forecasting performance of support vector machines (SVM) model. This paper presents the combining model (PSO-SVM) of the particle swarm optimization and support vector machine. This model uses the PSO to conduct the optimization...
Feature extraction is an important task before weapon system cost forecasting modeling, which affects the forecasting performance of the model. In this paper, feature extraction in the weapon system cost forecasting was studied. In regard to the mechanism of feature extraction and the good performance of support vector machine (SVM), principal components analysis (PCA) and kernel principal components...
A novel model was proposed for short-term electricity price forecasting based on rough set approach and improved support vector machines (SVM). Firstly, we can get reduced information table with no information loss by rough set approach. And then, this reduced information is used to develop classification rules and train SVM, at the same time, we make use of the particle swarm optimization to optimize...
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