The Fuzzy Reasoning Algorithm

The Fuzzy reasoning algorithm for the Adaptive Fuzzy Petri Nets is stated as detailed below as:

Step 1

Build the set of user input places PUI.

Step 2

Build the set of initially embedded transitions Tp.

Step 3

Determine the current enabled transitions

 Step 4

 T_f = {t ∈ T_p | for ∀p_i ∈    t, α (p_i) ≥ λi }

Determine all the current enabled transitions and compute innovative certainty factors that are generated via fired transitions.

Step 5

Make token transmission. Suppose p is one of the output places of the fired transition

• If | p | = 1 then add a token to p along with the certainty factor that is generated by its input transition;
• If | p | ≥ 1 and more than one of its input transitions fired, then decide the transition along with the maximum output weight, and add a token to p along with certainty factor produced via this transition.

Step 6

Suppose T = T - T_f , P = P - T_f .

Step 7

If T_f ≠ φ then repeats Steps 2 to 6 else go to Step 8.

Step 8

Stop.