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Due to the complexity of crude oil price series, traditional statistics-based forecasting approach cannot produce a good prediction performance. In order to improve the prediction performance, a novel compressed sensing based learning paradigm is proposed through integrating compressed sensing based denoising (CSD) and certain artificial intelligence (AI), i.e., CSD-AI. In the proposed learning paradigm,...
Crude oil price forecasting has been a difficult challenge for years. To improve the forecasting performance, a novel forecasting method is proposed through combining compressed sensing based denoising (CSD) approach and least square support vector regression (LSSVR) forecasting model. In the forecasting model, the grid search algorithm is used to optimize the parameter of LSSVR. Compared with the...
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