<![CDATA[This study aims to compare the Fuzzy Mamdani and Tsukamoto methods in estimating electricity consumption in Romania during the period 2019-2024. Daily electricity consumption data were obtained from the Kaggle dataset, which records electricity production and consumption based on energy source types. The Mamdani method employs triangular membership functions to define rules and provides output in the form of membership degrees for low, medium, and high efficiency levels. On the other hand, the Tsukamoto method utilizes a linear membership function-based approach to compute output based on direct correlations between input variables and output. Comparative analysis reveals differences in the accuracy and sensitivity of both methods to variations in electricity consumption data. The findings highlight the strengths and weaknesses of each method in the context of complex electricity consumption predictions.]]>
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