AKTU Introduction to Soft Computing (KOE046) Question Paper 2021-22

Note: Attempt all Sections. If you require any missing data, then choose suitably.

Section A

Q1. Attempt all questions in brief · 2 × 10 = 20 marks

1. Explain the differences between artificial and biological neurons.
2. What is soft computing? What distinguishes it from traditional computing?
3. What are some examples of fuzzy logic's applications?
4. Distinguish between crisp and fuzzy sets.
5. What is defuzzification and why is it required? Explain mean of maxima and center of sum method.
6. Differentiate between probability theory and Fuzzy set theory.
7. How do genetic algorithms perform more effectively than conventional methods?
8. Explain genetic algorithms' Roulette Wheel Selection in a few words.
9. What is crossover in genetic algorithm.
10. What is the use of mutation in genetic algorithm?

Section B

Q2. Attempt any three of the following · 10 × 3 = 30 marks

1. Describe artificial neural network multilayer perceptron model.
2. Let A and B be two fuzzy sets given by A: {(x1, 0.2), (x2,0.5), (x3, 0.6)}; B : {(x1, 0.1), (x2,0.4), (x3,0.5)}. Find (A-B) .
3. What will the input and output be for an air conditioner in a fuzzy controller?
4. Define the generation cycle. Describe the various applications of genetic algorithms.
5. How soft computing can be used in internet search techniques? Explain with suitable example.

Section C

Q3

Attempt any one part of the following · 10 × 1 = 10 marks

1. Explain the Hopfield network with an example.
2. Discuss about the supervised learning strategy.

Q4

Attempt any one part of the following · 10 × 1 = 10 marks

1. Give reasons for using fuzzy logic in AI. List a few examples from the world of industry where fuzzy logic is utilized for control.
2. Let X = {a, b, c, d} Y={1,2,3,4} And the three fuzzy sets be given as: Calculate the implication relation i IF x is Fuzzy set A THEN y is Fuzzy set B ii IF x is Fuzzy set A THEN y is Fuzzy set B ELSE y is Fuzzy set C.

Q5

Attempt any one part of the following · 10 × 1 = 10 marks

1. Two fuzzy sets I and F are defined as:
   I = {(F,0.4), (E,0.3), (X,0.1), (Y,0.1), (I,0.9), (T,0.8)}
F = {(F,0.99), (E,0.8), (X,0.1), (Y,0.2), (I,0.5), (T,0.5)}
   Determine the following:
   i.) Fuzzy set I – Fuzzy set F ii.) Verify (De Morgan’s Law) following: Complement of (Fuzzy
2. Illustrate various defuzzification methods in details.

Q6

Attempt any one part of the following · 10 × 1 = 10 marks

1. Explain rank selection and Roulette wheel selection methods.
2. What exactly do genetic bitwise operators do? Explain.

Q7

Attempt any one part of the following · 10 × 1 = 10 marks

1. Propose a solution to travelling salesman problem using genetic algorithm.
2. What two requirements should a problem satisfy in order to be suitable for solving it by a GA?

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