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Self CNN-based time series stream forecasting

Self CNN-based time series stream forecasting

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Self-learning convolutional neural network (self-CNN) for time series stream forecasting is proposed. First, the proposed self-CNN model was trained using the different types of the time series data. With the lapse of the time series stream the self-CNN model was self-trained again and again, which was using the previously predicted correct data as the input. Finally, the model was used to forecast the new time series data. The performance evaluation using the self-CNN method forecast and generate from the financial time series stream shows that the proposed self-CNN method performs better than the traditional Bollinger bands method.

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http://iet.metastore.ingenta.com/content/journals/10.1049/el.2016.2626
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