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 : Click on Discuss to view users comments. |
The membership functions are generally represented in
A. | Tabular Form |
B. | Graphical Form |
C. | Mathematical Form |
D. | Logical Form |
Option: B Explanation : Click on Discuss to view users comments. |
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 : Click on Discuss to view users comments. |
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 : Click on Discuss to view users comments. |
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