Download PTU M.Tech. ECE 2nd Semester 76068 SOFT COMPUTING TECHNIQUES Question Paper

Download PTU. I.K. Gujral Punjab Technical University (IKGPTU) M.Tech. ECE 2nd Semester 76068 SOFT COMPUTING TECHNIQUES Question Paper.

1 | M-76068 (S35)-848

Roll No. Total No. of Pages : 01
Total No. of Questions : 08
M.Tech. ECE (Wireless Communication) (2018 Bach) (Sem.?2)
SOFT COMPUTING TECHNIQUES
Subject Code : MTWC-104-18
M.Code : 76068
Time : 3 Hrs. Max. Marks : 60

INSTRUCTIONS TO CANDIDATES :
1.Attempt any FIVE questions out of EIGHT questions.
2.Each question carries TWELVE marks.

Q.l (a) Define soft computing and explain the importance of soft computing in the field of
machine learning. [6]
(b) List various learning schemes and explain any one of them with example. [6]
Q.2 (a) What is pattern classification? Explain one of the algorithms for pattern classification
in detail. [6]
(b) Draw and explain McCulloch-Pitts model of neural network with its limitations. [6]
Q.3 (a) Differentiate perceptron and Hebbian learning algorithms with an appropriate
example. [6]
(b) Draw and explain ADALINE network with its application? [6]
Q.4 What is travelling sales man problem? List the possible solutions for this task and explain
one of the best algorithms with suitable example in detail. [12]
Q.5 (a) Draw and explain recurrent neural network with its real life application. [6]
(b) What is the significance of adaptive resonance theory neural network? Draw and
explain ART1 neural network with suitable example. [6]
Q.6 (a) What are the differences between derivative free and derivative based optimization
algorithms? [6]
(b) What is fuzzification processes? Explain one of the popular fuzzification processes in
detail with suitable example. [6]
Q.7 (a) Discuss the importance of hybrid soft computing techniques in machine learning. [6]
(b) Explain GA based BPNN hybrid Softcomputing scheme with an example. [6]
Q.8 (a) Differentiate between classical and Fuzzy sets. Explain two important operations on
classical and fuzzy sets with example. [6]
(b) Explain multiobjective optimization using genetic algorithm with an example. [6]
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