M.C.A.(R)/M.C.A.(WE) DEGREE EXAMINATION,
APRIL 2017
Fourth Semester
SOFT COMPUTING
(2012 onwards)
Time 3 Hours Maximum 75 Marks
Part A (10 X 2 20)
Answer all questions.
1. How does soft computing differ from hard computing?
2. What are the different learning paradigms?
3. List out the various activation function used in ANN.
4. What is an auto associative network?
5. Enumerate the demerits of back propagation algorithm.
6. State defuzzification techniques.
7. What is the main difference between probability and
fuzzy logic?
8. What is meant by fuzzy measure?
9. What is genetic algorithm?
10. What are the elements of Genetic algorithm?
Sub. Code
541561/
545561
RW-162
2
Wk6
Part B X 5 25)
Answer all questions, choosing either or
11. Describe about the application scope of neural
networks.
Or
Explain briefly about the categories of learning in
ANN.
12. Explain about the Adaline network
Or
Discuss about the Hopfield network.
13. Differentiate between Crisp set and Fuzzy set.
Or
Explain about Fuzzy relation.
14. Explain the use of fuzzy measure.
Or
How to make a Process of developing a fuzzy expert
system?
15. Describe about Encoding in genetic algorithm.
Or
Explain about the Inversion and Deletion in GA.
Part C X 10 30)
Answer any three questions.
16. Explain briefly about the Neural network Architecture.
17. Describe briefly about an Architecture of Back
propagation Network.
RW-162
3
Wk6
18. Explain briefly about the Defuzzification method.
19. Discuss about the Mamdani-style fuzzy inference process.
20. Explain about the Cross over in GA.
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