Welcome to the Fuzzy Systems MCQs Page

Dive deep into the fascinating world of Fuzzy Systems with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Fuzzy Systems, a crucial aspect of UGC CBSE NET Exam. In this section, you will encounter a diverse range of MCQs that cover various aspects of Fuzzy Systems, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within UGC CBSE NET Exam.

Check out the MCQs below to embark on an enriching journey through Fuzzy Systems. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of UGC CBSE NET Exam.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Fuzzy Systems. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Fuzzy Systems MCQs | Page 1 of 3

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Q1.

Consider a fuzzy set A defined on the interval X = [0, 10] of integers by the membership Junction
μA(x) = x / (x+2)
Then the α cut corresponding to α = 0.5 will be

{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10}

{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}

{2, 3, 4, 5, 6, 7, 8, 9, 10}

None of the above

Discuss

Answer: (c).{2, 3, 4, 5, 6, 7, 8, 9, 10}

Q2.

If A and B are two fuzzy sets with membership functions:

μa(χ) ={0.2,0.5.,0.6,0.1,0.9}

μb (χ)= {0.1,0.5,0.2,0.7,0.8}

then the value of μa ∩ μb will be

{0.2,0.5,0.6,0.7,0.9}

{0.2, 0.5,0.2, 0.1,0.8}

{0.1, 0.5, 0.6, 0.1,0.8}

{0.1, 0.5, 0.2, 0.1,0.8}

Discuss

Answer: (d).{0.1, 0.5, 0.2, 0.1,0.8}

Q3.

The height h(A) of a fuzzy set A is defined as

h(A) = sup A(x)

h(A) = 0

h(A) <0

h(A)=1

h(A)<1

Discuss

Answer: (c).h(A)=1

Q4.

A __________ point of a fuzzy set A is a point x ∈ X at which µA(x) = 0.5

Core

Support

Cross-over

α - cut

Discuss

Answer: (c).Cross-over

Q5.

Suppose the function y and a fuzzy integer number around -4 for x are given as y= (x-3)2 + 2.

Around -4 = {(2, 0.3), (3, 0.6), (4, 1), (5, 0.6), (6, 0.3)} respectively. Then f (Around -4) is given by:

{(2, 0.6), (3, 0.3), (6, 1), (11, 0.3)}

{(2, 0.6), (3, 1), (6, 1), (11, 0.3)}

{(2, 0.6), (3, 1), (6, 0.6), (11, 0.3)}

{(2, 0.6), (3, 0.3), (6, 0.6), (11, 0.3)}

Discuss

Answer: (c).{(2, 0.6), (3, 1), (6, 0.6), (11, 0.3)}

Q6.

Given U = {1,2,3,4,5,6,7}

A = {(3, 0.7), (5, 1), (6, 0.8)}

then A will be: (where ~ → complement)

{(4, 0.7), (2,1), (1,0.8)}

{(4, 0.3.): (5, 0), (6. 0.2) }

{(l, 1), (2, 1), (3, 0.3), (4, 1), (6,0.2), (7, 1)}

{(3, 0.3), (6.0.2)}

Discuss

Answer: (c).{(l, 1), (2, 1), (3, 0.3), (4, 1), (6,0.2), (7, 1)}

Q7.

Consider a fuzzy set old as defined below

Old = {(20, 0.1), (30, 0.2), (40, 0.4), (50, 0.6), (60, 0.8), (70, 1), (80, 1)}

Then the alpha-cut for alpha = 0.4 for the set old will be

{(40,0.4)}

{50, 60, 70, 80}

{(20, 0.1), (30, 0.2)}

{(20, 0), (30, 0), (40, 1), (50,1), (60, 1), (70, 1), (80, 1)}

Discuss

Answer: (d).{(20, 0), (30, 0), (40, 1), (50,1), (60, 1), (70, 1), (80, 1)}

Q8.

Perceptron learning, Delta learning and LMS learning are learning methods which falls under the category of

Error correction learning - learning with a teacher

Reinforcement learning - learning with a critic

Hebbian learning

Competitive learning - learning without a teacher

Discuss

Answer: (a).Error correction learning - learning with a teacher

Q9.

Let R and S be two fuzzy relations defined as follows. Then, the resulting relation, T, which relates elements of universe x to the elements of universe z using max-min composition is given by:

(1)

(2)

(3)

(4)

Discuss

Answer: (c).(3)

Q10.

What are the following sequence of steps taken in designing a fuzzy logic machine ?

Fuzzification → Rule evaluation → Defuzzification

Fuzzification → Defuzzification → Rule evaluation

Rule evaluation → Fuzzification → Defuzzification

Rule evaluation → Defuzzification → Fuzzification

Discuss

Answer: (a).Fuzzification → Rule evaluation → Defuzzification

Page 1 of 3

Welcome to the Fuzzy Systems MCQs Page

Fuzzy Systems MCQs | Page 1 of 3

Explore more Topics under UGC CBSE NET Exam

Networking

Operating System

Software Engineering

Systems Programming

Data Structures and Algorithms

Computer Architecture

DBMS

Computer Graphics

Artificial Intelligence

Web Technologies

Theory of Computation(TOC)

Discrete Structures

Computer Arithmetic

Programming in C

UNIX System

Current Trends and Technologies

Neural Networks

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