1. Fuzzy logic is a form of
a) Two-valued logic
b) Crisp set logic
c) Many-valued logic
d) Binary set logic
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.
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
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.
5. How many types of random variables are available?
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
Explanation: Fuzzy logic deals with linguistic variables.
7. The values of the set membership is represented by
a) Discrete Set
b) Degree of truth
d) Both b & c
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
9. Japanese were the first to utilize fuzzy logic practically on high-speed trains in Sendai.
10. Which of the following is used for probability theory sentences?
a) Conditional logic
c) Extension of propositional logic
d) None of the mentioned
Explanation: The version of probability theory we present uses an extension of propositional logic for its sentences.
Sanfoundry Global Education & Learning Series – Artificial Intelligence.