a) Either 0 or 1, between 0 & 1
Explanation: Refer the definition of Fuzzy set and Crisp set.
Fuzzy logic is extension of Crisp set with an extension of handling the concept of Partial Truth. a) True b) False
Where do we implement Artificial Intelligence Fuzzy Logic?
What is Artificial Intelligence Fuzzy Logic?
Traditional set theory is also known as Crisp Set theory. a) True b) False
____________ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic. a) Fuzzy Relational DB b) Ecorithms c) Fuzzy Set d) None of the mentioned
Like relational databases there does exists fuzzy relational databases. a) True b) False
What is the consequence between a node and its predecessors while creating Bayesian network? a) Conditionally dependent b) Dependent c) Conditionally independent d) Both a & b
Fuzzy logic is usually represented as a) IF-THEN-ELSE rules b) IF-THEN rules c) Both a & b d) None of the mentioned
_____________ is/are the way/s to represent uncertainty. a) Fuzzy Logic b) Probability c) Entropy d) All of the mentioned
What does the Bayesian network provides? a) Complete description of the domain b) Partial description of the domain c) Complete description of the problem d) None of the mentioned
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