# FORECASTING ELECTRICITY PRODUCTION USING FUZZY LOGIC

The forecasting accuracy obtained by the method using the model of invariant fuzzy time series and fuzzy implications for solving the problem of electricity production forecasting does not meet modern requirements. Moreover, complex calculations are used in operations related to fuzzy implications, which are used to obtain forecast results and form a matrix of fuzzy relations. The paper proposes a new method for obtaining more accurate forecasting results using simple computational operations to solve the problem of electricity production forecasting by dividing the universal set into different numbers of equal intervals based on fuzzy time series. The proposed method uses the method of averaged differences, which simplifies the calculation of forecast results. This method, which is determined by the statistics related to different numerical equal intervals, can be used to justify both the distribution of universal set and to find the optimal number of linguistic terms in this regard. The effectiveness of this method is justified by calculating the results of electricity production forecasting through the proposed method (pp.30-40).

Keywords: Fuzzy set, fuzzy time series, Average forecasting error rate, Mean square error.
DOI : 10.25045/jpit.v12.i2.03
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