What Is Fuzzy Logic?

Building Fuzzy Inference Systems Using Custom Functions
variables, and nr is the number of rules. The output of the aggregation
method is one fuzzy set for each output variable.
The following is an example of a custom aggregation function:
function aggfun = custom_agg(x)
aggfun=(sum(x)/2).^0.5;
Guidelines for Creating Custom Defuzzification Functions
The custom defuzzification functions must be of the form y =
custom_defuzz(xmf,ymf), where(xmf,ymf) is a finite set of membership
function values. xmf is the vector of values in the membership function input
range. ymf is the value of the membership function at xmf.
The following is an example of a custom defuzzification function:
function defuzzfun= custom_defuzz(xmf,ymf);
total_area=sum(ymf);
defuzzfun=sum(ymf*xmf)/total_area;
Steps for Specifying Custom Inference Functions
After you create and save a custom inference function, use the following steps
to specify the function in the fuzzy inference process:
2-69