The article is devoted to the problem of applying the formal data mining toolforecastingfor the developing of new software and for reengineering the present software. We propose the algorithm adjustments of the time series forecasting. This algorithm takes into account the dependence of the current state of time series from the previous one, the influence of basic fuzzy projected trends in the time series. The proposed algorithm expands the opportunities of time series short-term forecasting on the base of fuzzy trends, as the historical software time series are of small length. The proposed algorithm was examined experimentally and showed the efficiency
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