Exploring Fuzzy Associative Models: A Fuzzy Logic Approach to Handling Complex, Uncertain Data
DOI:
https://doi.org/10.64137/3108-2637/IJMAR-V2I2P101Keywords:
FAM, AI, Memory, Data, Output variablesAbstract
Fuzzy Associative Models (FAMs) leverage fuzzy logic to effectively represent uncertain and imprecise knowledge in a compact, interpretable form. By accommodating the inherent ambiguity of real-world data, FAMs excel in applications where relationships between variables are complex, nonlinear, and uncertain. This makes them a powerful tool for handling real-world complexities, enabling more nuanced decision-making and problem-solving in fields like AI, data analysis, and beyond.
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