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Erschienen in:
2011 | OriginalPaper | Buchkapitel
An Improved EMD Online Learning-Based Model for Gold Market Forecasting
verfasst von : Shifei Zhou, Kin Keung Lai
Erschienen in: Intelligent Decision Technologies
Verlag: Springer Berlin Heidelberg
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In this paper, an improved EMD (Empirical Mode Decomposition) online learning-based model for gold market forecasting is proposed. First, we adopt the EMD method to divide the time series data into different subsets. Second, a back-propagation neural network model (BPNN) is used to function as the prediction model in our system. We update the online learning rate of BPNN instantly as well as the weight matrix. Finally, a rating method is used to identify the most suitable BPNN model for further prediction. The experiment results show that our system has a good forecasting performance.