Fuzzy inference is the actual process that brings everything together to formulate the actions for the intelligent machines. The process can be depicted as follows:
In traditional systems, the inputs are received as crisp sets. The crisp input are fuzzified as membership functions and the input fuzzy sets are aggregated with union/complement/differentiation techniques. Once the aggregated membership function is obtained, we apply the knowledge base, rules, and utilize historical datasets before defuzzifying the input set into an actionable output value.
Modern intelligent systems need to work with fuzzy input directly; the ...
