What is fuzzification? Explain with an example.

 

Answer: For each input and output variable selected, we define we or more membership function (MF), normally three but can be more. We have to define a qualitative category for each one of them, for example: low, normal or high.

Example 1: If we take x like a variable and low, normal and high as trapezoidal, triangle and trapezoidal MFs, respectively

-          The MF low will be defined by three points: (x1, x2, x3). However, in order to have a real trapezoid, we need a four point at the left x1 (any negative one, e.g., x0)

-          Following the same reasoning, the MF high will be defined by four points: (x3, x4, x5, x6) (x6 any positive > x5, being x5 the higher possible value for x)

-          Finally, the MF normal (like any other triangular MF) will be defined by three points: (x2, x3, x4).

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