FACULTY OF ENGINEERING B.E. 4/4 (CSE) II – Semester (Main) Examination, April / May 2013 Subject : Soft Computing
(Elective – II)
Time : 3 hours
Max. Marks : 75
Note: Answer all questions from Part-A. Answer any FIVE questions from Part-B. PART – A (25 Marks) 1. Briefly explain what is an artificial neuron.
3
2. What is the importance of threshold in perception network.
2
3. Define Delta rule.
2
4. List out the benefits of neural networks.
3
5. Describe unsupervised learning.
2
6. What is an XOR problem?
3
7. Discuss the methods of aggregation of fuzzy ruler.
3
8. What is meant by cross over point in a fuzzyset?
2
9. Compare and contrast traditional algorithm and genetic algorithm.
3
10. What is genetic programming?
2
PART – B (5 x 10 = 50 Marks) 11.a) What is a learning rate parameter? b) State the training algorithm used for Hebb network.
3 7
12.a) What is meant by gradient descent method? b) List the stages involved in training of backpropagation network.
4 6
13.a) State the advantages of associative memory. b) Draw the architecture of discrete Hopfield net.
4 6
14. Explain the training algorithm used in ART network. 15.a) Define fuzzy number. b) Describe how neural network is used to obtain fuzzy membership functions. 16. Explain the working of genetic algorithms with suitable example. 17. Write short notes on the following : a) Fuzzy ordering b) Applications of genetic algorithms ******
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