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QPSO-LSTM Based Electricity Sales Forecasting Model
This paper gives a review of the recent developments in deep learning and un-supervised feature learning for time-series problems. While these techniques have shown promise for modeling static data, such as computer vision, ap-plying them to time-series data is gaining increasing attention. This paper overviews the particular challenges present in time-series data and provides a review of the works that have either applied time-series data to unsupervised feature learning algorithms or alternatively have contributed to modications of feature learning algorithms to take into account the challenges present in time-series data.
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