VTG schemes for using back propagation for multivariate time series prediction

This research proposes the three schemes of estimating and adding mid-terms to multivariate time series. In this research, the back propagation is adopted as the approach to multivariate time series prediction. It is traditionally designed for the task with the two models: separated model and combined model. In the proposed version of time series prediction systems, the mid-term estimator is added as the additional module to the traditional version. It is validated empirically that the three VTG (Virtual Term Generation) schemes are effective on using the back propagation for multivariate time series prediction on the four test data sets: three artificial one and a real test one.

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► We set the multivariate time series prediction as the task of this article.
► We generate the virtual terms in the time series using equations based on interpolation equations.
► We generate the training examples from the series two times than from one without generating virtual terms.
► We improve the prediction performance by doing so.