Q1.
a) What do you mean by the term soft computing? Illustrate the different constituents of soft computing methodology? In brief explain the strengths of each of such methodologies.
b) With Neuro-fuzzy modeling as a backbone, explain at least five features of the soft computing.
Q2.
a) Let R and S be two fuzzy relations illustrated below:
0.3 0.8 0.4
R = 0.6 0.9 0.1
0.2 0.5 0.6
0.2 0.8 0.4
S = 0.7 0.9 0.1
0.8 0.3 0.5
i) If R = “x considerably bigger than y” and S= “y very close to x” then give the matrices defining the fuzzy relations “x considerably bigger or very close to y” and “x considerably bigger and very close to y”
ii) Find out the composition relation RoS.
b) Give fuzzy logic inference method for the given rule under the fuzzy logic. The rule is as follows:
IF A THEN B ELSE C where A = very small, B = very large and C = NOT very large.
Small and large are defined as under
Small = 1/1+0.8/2+0.4/3+0.2/4+0/5
Large = 0/1+0/2+0/4+0.8/4+1/5
If A has size = 4, then what would be the resulting inference