The values of the set membership is represented by
a) Discrete Set
b) Degree of truth
c) Probabilities
d) Both b & c
Why fuzzy logic?
Where do we implement artificial intelligence fuzzy logic?
Fuzzy logic is extension of Crisp set with an extension of handling the concept of Partial Truth. 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
Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following. a) AND b) OR c) NOT d) EX-OR
The room temperature is hot. Here the hot (use of linguistic variable is used) can be represented by _______ . a) Fuzzy Set b) Crisp Set
Japanese were the first to utilize fuzzy logic practically on high-speed trains in Sendai. a) True b) False
What is artificial intelligence fuzzy logic?
The truth values of traditional set theory is ____________ and that of fuzzy set is __________ a) Either 0 or 1, between 0 & 1 b) Between 0 & 1, either 0 or 1 c) Between 0 & 1, between 0 & 1 d) Either 0 or 1, either 0 or 1
Like relational databases there does exists fuzzy relational databases. a) True b) False
Fuzzy logic is a form of a) Two-valued logic b) Crisp set logic c) Many-valued logic d) Binary set logic
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