At the core of the ANFIS architecture is the adaptive network that uses the supervised learning algorithm. Let's understand this with a simple example. Consider that there are two inputs, x and y, and an output, z. We can consider the use of two simple rules in the method of if-then as follows:
Rule 1: If x is A1 and y is B1 then z1 = p1x + q1x + r1
Rule 2: If x is A2 and y is B2 then z2 = p2y + q2y + r2
A1, A2 and B1, B2 are the membership functions of each input x and y. p1, q1, r1 and p2, q2, r2 are linear parameters of the fuzzy inference model.
Let's illustrate this with a diagram:
The ...
