If put all groups of the historical feature patterns into a new long sequence, and repeat above prediction, then the performance of ARMA and GM(1, 1) drops rapidly, and that of HFPE does not change much for that longer sequence containing more correlation is benefit to prediction.
It can be found from the table data that HFPE has the best performance among the four algorithms.
This paper proposes a prediction method based on historical feature pattern, that is, HFPE. The main principle of this algorithm is shown as follows.