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Recently, variational mode decomposition (VMD) has been proposed as an advanced multiresolution technique for signal processing. This study presents a VMD-based generalized regression neural network ensemble learning model to predict California electricity and Brent crude oil prices. Its performance is compared to that of the empirical mode decomposition (EMD) based generalized regression neural network...
Among financial time-series analysis tasks, stock index forecasting has been considered as one of the challenging and difficult tasks. Since an accurate stock index prediction enhances stock market returns, it is highly promising research area and has attracted particular attention. In this paper, to predict stock index with complex and nonlinear characteristics, an automatic structure identification...
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