View Source Flex.EngineAdapter.TakagiSugeno (FLex v0.2.0)

Takagi-Sugeno-Kang fuzzy inference uses singleton output membership functions that are either constant or a linear function of the input values. The defuzzification process for a Sugeno system is more computationally efficient compared to that of a Mamdani system, since it uses a weighted average or weighted sum of a few data points rather than compute a centroid of a two-dimensional area.

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Functions

Turns an consequent fuzzy variable (output) from a fuzzy value to a crisp value (weighted average method).

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inference_engine(fuzzy_antecedent, list, consequent)

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weighted_average_method(fuzzy_var)

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@spec weighted_average_method(Flex.Variable.t()) :: float()

Turns an consequent fuzzy variable (output) from a fuzzy value to a crisp value (weighted average method).