Artificial Intelligence Fuzzy Logic Interview Preparation Guide

Strengthen your Artificial Intelligence Fuzzy Logic interview skills with our collection of 22 important questions. These questions are specifically selected to challenge and enhance your knowledge in Artificial Intelligence Fuzzy Logic. Perfect for all proficiency levels, they are key to your interview success. Access the free PDF to get all 22 questions and give yourself the best chance of acing your Artificial Intelligence Fuzzy Logic interview. This resource is perfect for thorough preparation and confidence building.
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22 Artificial Intelligence Fuzzy Logic Questions and Answers:

1 :: What is Artificial Intelligence Fuzzy Logic?

Fuzzy logic is a form of many-valued logic; it deals with reasoning that is approximate rather than fixed and exact. In contrast with traditional logic theory, where binary sets have two-valued logic: true or false, fuzzy logic variables may have a truth value that ranges in degree between 0 and 1. Fuzzy logic has been extended to handle the concept of partial truth, where the truth value may range between completely true and completely false. Furthermore, when linguistic variables are used, these degrees may be managed by specific functions.
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2 :: Where do we implement Artificial Intelligence Fuzzy Logic?

It's a multi valued logic.
In Boolean logic is two valued logic,where we will say
an element belongs to a set with membership 1, if it
doesn't belongs to the set then it's membership is 0.

Where as in fuzzy sets we say degree of membership
between 0 and 1.

For example,we have a set of men age.
In Boolean logic a person X aged 51 we will say x is old
and a person Y aged 49 we will say young.
In fuzzy logic we say X belongs to the old men set with a
membership of 0.51 and to young men set with a membership of
0.49

So Boolean logic is our Black&White TV where as Fuzzy logic
is Color TV Fuzzy logic is a Discrete spectrum of values.

3 :: 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

c) Many-valued logic
Explanation: With fuzzy logic set membership is defined by certain value. Hence it could have many values to be in the set.

4 :: 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

a) Either 0 or 1, between 0 & 1
Explanation: Refer the definition of Fuzzy set and Crisp set.

5 :: Fuzzy logic is extension of Crisp set with an extension of handling the concept of Partial Truth.
a) True
b) False

a) True
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6 :: How many types of random variables are available?
a) 1
b) 2
c) 3
d) 4

c) 3
Explanation: The three types of random variables are Boolean, discrete and continuous.

7 :: The room temperature is hot. Here the hot (use of linguistic variable is used) can be represented by _______ .
a) Fuzzy Set
b) Crisp Set

a) Fuzzy Set
Explanation: Fuzzy logic deals with linguistic variables.

8 :: The values of the set membership is represented by
a) Discrete Set
b) Degree of truth
c) Probabilities
d) Both b & c

b) Degree of truth
Explanation: Both Probabilities and degree of truth ranges between 0 - 1.

9 :: What is meant by probability density function?
a) Probability distributions
b) Continuous variable
c) Discrete variable
d) Probability distributions for Continuous variables

d) Probability distributions for Continuous variables

10 :: Japanese were the first to utilize fuzzy logic practically on high-speed trains in Sendai.
a) True
b) False

a) True
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