Classical

Soft Computing - Membership Functions

1:  

Membership function defines the fuzziness in a fuzzy set irrespective of the elements in the set, which are discrete or continuous.

A.

True

B.

False

C.
D.
 
 

Option: A

Explanation :


2:  

The membership functions are generally represented in

A.

Tabular Form

B.

Graphical Form

C.

Mathematical Form

D.

Logical Form

 
 

Option: B

Explanation :


3:  

Membership function can be thought of as a technique to solve empirical problems on the basis of

A.

knowledge

B.

examples

C.

learning

D.

experience

 
 

Option: D

Explanation :


4:  
Three main basic features involved in characterizing membership function are
A.

Intution, Inference, Rank Ordering

B.

Fuzzy Algorithm, Neural network, Genetic Algorithm

C.

Core, Support , Boundary

D.

Weighted Average, center of Sums, Median

 
 

Option: C

Explanation :


5:  

The region of universe that is characterized by complete membership in the set  is called

A.

Core

B.

Support

C.

Boundary

D.

Fuzzy

 
 

Option: A

Explanation :




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