Abstract
The article proposes an original entropy time series (TS) model, as well as an entropy time series (ETS) predictive algorithm. The model is built in the form of a set of points, each containing a pair of values, a measure of entropy based on the TS point and the dynamics of entropy at a point in comparison with the previous point of the set. The forecasting algorithm based on the ETS is based on the forecast by any of the available methods for forecasting the TS, built from the dynamics values calculated for the entropy points and from calculating the predicted value through the predicted dynamics value and the entropy value at the last point of the series. The predicted value obtained by the above algorithm is proposed to be used as a correction value when predicting TS by any of the available forecasting methods. This approach has been tested on TSs offered at the IRAFM 2015.
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