Artificial Intelligence Questions and
Answers – Fuzzy Logic – 1
This set of Artificial Intelligence MCQs focuses on “Fuzzy Logic – 1”.
1. Fuzzy logic is a form of
a) Two-valued logic
b) Crisp set logic
c) Many-valued logic
d) Binary set logic
View Answer
Answer: c
Explanation: With fuzzy logic set membership is defined by certain value. Hence it
could have many values to be in the set.
2. Traditional set theory is also known as Crisp Set theory.
a) True
b) False
View Answer
Answer: a
Explanation: Traditional set theory set membership is fixed or exact either the
member is in the set or not. There is only two crisp values true or false. In case of
fuzzy logic there are many values. With weight say x the member is in the set
3. 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
View Answer
Answer: a
Explanation: Refer the definition of Fuzzy set and Crisp set.
4. Fuzzy logic is extension of Crisp set with an extension of handling the concept of
Partial Truth.
a) True
b) False
View Answer
Answer: a
Explanation: None.
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,5. How many types of random variables are available?
a) 1
b) 2
c) 3
d) 4
View Answer
Answer: c
Explanation: The three types of random variables are Boolean, discrete and
continuous.
6. The room temperature is hot. Here the hot (use of linguistic variable is used) can be
represented by _______ .
a) Fuzzy Set
b) Crisp Set
View Answer
Answer: a
Explanation: Fuzzy logic deals with linguistic variables.
7. The values of the set membership is represented by
a) Discrete Set
b) Degree of truth
c) Probabilities
d) Both b & c
View Answer
Answer: b
Explanation: Both Probabilities and degree of truth ranges between 0 – 1.
8. What is meant by probability density function?
a) Probability distributions
b) Continuous variable
c) Discrete variable
d) Probability distributions for Continuous variables
View Answer
Answer: d
Explanation: None.
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9. Japanese were the first to utilize fuzzy logic practically on high-speed trains in
Sendai.
a) True
b) False
View Answer
Answer: a
Explanation: None.
10. Which of the following is used for probability theory sentences?
a) Conditional logic
,b) Logic
c) Extension of propositional logic
d) None of the mentioned
View Answer
Answer: c
Explanation: The version of probability theory we present uses an extension of
propositional logic for its sentences.
Artificial Intelligence Questions and
Answers – Fuzzy Logic – 2
This set of Artificial Intelligence MCQs focuses on “Fuzzy Logic – 2”.
1. Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the
following.
a) AND
b) OR
c) NOT
d) EX-OR
View Answer
Answer: a, b, c
Explanation: The AND, OR, and NOT operators of Boolean logic exist in fuzzy logic,
usually defined as the minimum, maximum, and complement;
2. There are also other operators, more linguistic in nature, called __________ that
can be applied to fuzzy set theory.
a) Hedges
b) Lingual Variable
c) Fuzz Variable
d) None of the mentioned
View Answer
Answer: a
Explanation: None.
3. Where does the Bayes rule can be used?
a) Solving queries
b) Increasing complexity
c) Decreasing complexity
d) Answering probabilistic query
View Answer
Answer: d
Explanation: Bayes rule can be used to answer the probabilistic queries conditioned
on one piece of evidence.
, 4. 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
View Answer
Answer: a
Explanation: A Bayesian network provides a complete description of the domain.
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5. Fuzzy logic is usually represented as
a) IF-THEN-ELSE rules
b) IF-THEN rules
c) Both a & b
d) None of the mentioned
View Answer
Answer: b
Explanation: Fuzzy set theory defines fuzzy operators on fuzzy sets. The problem in
applying this is that the appropriate fuzzy operator may not be known. For this reason,
fuzzy logic usually uses IF-THEN rules, or constructs that are equivalent, such as
fuzzy associative matrices.
Rules are usually expressed in the form:
IF variable IS property THEN action
6. Like relational databases there does exists fuzzy relational databases.
a) True
b) False
View Answer
Answer: a
Explanation: Once fuzzy relations are defined, it is possible to develop fuzzy
relational databases. The first fuzzy relational database, FRDB, appeared in Maria
Zemankova’s dissertation.
7. ______________ is/are the way/s to represent uncertainty.
a) Fuzzy Logic
b) Probability
c) Entropy
d) All of the mentioned
View Answer
Answer: d
Explanation: Entropy is amount of uncertainty involved in data. Represented by
H(data).
8. ____________ are algorithms that learn from their more complex environments
(hence eco) to generalize, approximate and simplify solution logic.
a) Fuzzy Relational DB
b) Ecorithms
Answers – Fuzzy Logic – 1
This set of Artificial Intelligence MCQs focuses on “Fuzzy Logic – 1”.
1. Fuzzy logic is a form of
a) Two-valued logic
b) Crisp set logic
c) Many-valued logic
d) Binary set logic
View Answer
Answer: c
Explanation: With fuzzy logic set membership is defined by certain value. Hence it
could have many values to be in the set.
2. Traditional set theory is also known as Crisp Set theory.
a) True
b) False
View Answer
Answer: a
Explanation: Traditional set theory set membership is fixed or exact either the
member is in the set or not. There is only two crisp values true or false. In case of
fuzzy logic there are many values. With weight say x the member is in the set
3. 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
View Answer
Answer: a
Explanation: Refer the definition of Fuzzy set and Crisp set.
4. Fuzzy logic is extension of Crisp set with an extension of handling the concept of
Partial Truth.
a) True
b) False
View Answer
Answer: a
Explanation: None.
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,5. How many types of random variables are available?
a) 1
b) 2
c) 3
d) 4
View Answer
Answer: c
Explanation: The three types of random variables are Boolean, discrete and
continuous.
6. The room temperature is hot. Here the hot (use of linguistic variable is used) can be
represented by _______ .
a) Fuzzy Set
b) Crisp Set
View Answer
Answer: a
Explanation: Fuzzy logic deals with linguistic variables.
7. The values of the set membership is represented by
a) Discrete Set
b) Degree of truth
c) Probabilities
d) Both b & c
View Answer
Answer: b
Explanation: Both Probabilities and degree of truth ranges between 0 – 1.
8. What is meant by probability density function?
a) Probability distributions
b) Continuous variable
c) Discrete variable
d) Probability distributions for Continuous variables
View Answer
Answer: d
Explanation: None.
advertisements
9. Japanese were the first to utilize fuzzy logic practically on high-speed trains in
Sendai.
a) True
b) False
View Answer
Answer: a
Explanation: None.
10. Which of the following is used for probability theory sentences?
a) Conditional logic
,b) Logic
c) Extension of propositional logic
d) None of the mentioned
View Answer
Answer: c
Explanation: The version of probability theory we present uses an extension of
propositional logic for its sentences.
Artificial Intelligence Questions and
Answers – Fuzzy Logic – 2
This set of Artificial Intelligence MCQs focuses on “Fuzzy Logic – 2”.
1. Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the
following.
a) AND
b) OR
c) NOT
d) EX-OR
View Answer
Answer: a, b, c
Explanation: The AND, OR, and NOT operators of Boolean logic exist in fuzzy logic,
usually defined as the minimum, maximum, and complement;
2. There are also other operators, more linguistic in nature, called __________ that
can be applied to fuzzy set theory.
a) Hedges
b) Lingual Variable
c) Fuzz Variable
d) None of the mentioned
View Answer
Answer: a
Explanation: None.
3. Where does the Bayes rule can be used?
a) Solving queries
b) Increasing complexity
c) Decreasing complexity
d) Answering probabilistic query
View Answer
Answer: d
Explanation: Bayes rule can be used to answer the probabilistic queries conditioned
on one piece of evidence.
, 4. 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
View Answer
Answer: a
Explanation: A Bayesian network provides a complete description of the domain.
advertisements
5. Fuzzy logic is usually represented as
a) IF-THEN-ELSE rules
b) IF-THEN rules
c) Both a & b
d) None of the mentioned
View Answer
Answer: b
Explanation: Fuzzy set theory defines fuzzy operators on fuzzy sets. The problem in
applying this is that the appropriate fuzzy operator may not be known. For this reason,
fuzzy logic usually uses IF-THEN rules, or constructs that are equivalent, such as
fuzzy associative matrices.
Rules are usually expressed in the form:
IF variable IS property THEN action
6. Like relational databases there does exists fuzzy relational databases.
a) True
b) False
View Answer
Answer: a
Explanation: Once fuzzy relations are defined, it is possible to develop fuzzy
relational databases. The first fuzzy relational database, FRDB, appeared in Maria
Zemankova’s dissertation.
7. ______________ is/are the way/s to represent uncertainty.
a) Fuzzy Logic
b) Probability
c) Entropy
d) All of the mentioned
View Answer
Answer: d
Explanation: Entropy is amount of uncertainty involved in data. Represented by
H(data).
8. ____________ are algorithms that learn from their more complex environments
(hence eco) to generalize, approximate and simplify solution logic.
a) Fuzzy Relational DB
b) Ecorithms
