Dự báo tỉ giá ngoại tệ với mô hình học cộng đồng kết hợp giải thuật tiến hóa đa mục tiêu
Time series forecasting is paid a considerable attention of the researchers. At present, in the field of machine learning, there are a lot of studies using artificial neural networks to construct the model of time series forecast in general, and foreign currency exchange rates forecast, in particular. However, determining the number of members of an ensemble is still debatable. This paper proposes the way of constructing a model and designing a multi-objective evolutionary algorithm in training neural networks ensembles in order to increase the diversity of the population. Two objectives of the selected model include: Mean Sum of Squared Errors - MSE and Diversity. We experimented the model on four data sets and compared three methods (single-objective, multi- objective and ensembles). The experimental results showed that the proposed model produced better in investigated cases.
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