Download GTU (Gujarat Technological University) BE/BTech (Bachelor of Engineering / Bachelor of Technology) 2019 Winter 7th Sem New 2172009 Soft Computing Applications Previous Question Paper
Seat No.: ________ Enrolment No.___________
GUJARAT TECHNOLOGICAL UNIVERSITY
BE - SEMESTER ? VII (New) EXAMINATION ? WINTER 2019
Subject Code: 2172009 Date: 30/11/2019
Subject Name: Soft Computing Applications
Time: 10:30 AM TO 01:00 PM Total Marks: 70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
Q.1 (a) Do as directed.
(i) State the difference between soft computing and hard computing with
reference to its problem solving capabilities.
(ii) With the suitable example define & explain the supervised and
unsupervised learning method.
03
(b) Identify the basic traits of soft computing as computational process and briefly
explain how any one of these traits help us in problem solving of engineering
sector.
04
(c) Explain the basic membership functions of fuzzy sets with a suitable example. 07
Q.2 (a) Consider two fuzzy sets A and B as shown
1 0.5 0.3 0.2
2 3 4 5
A
??
? ? ? ?
??
??
and
0.5 0.7 0.2 0.4
2 3 4 5
B
??
? ? ? ?
??
??
Calculate several operation on the fuzzy set (i) AB ? (ii) AB ? (iii) A (iv) B
(v) cardinality and relative cardinality of fuzzy sets A and B
03
(b)
For the fuzzy sets given in Q.2(a) find out
(i) Algebraic product (ii) Bounded sum (iii) Bounded difference
(iv) Algebraic sum
04
(c) Consider two fuzzy relations R1 and R2 on XY ? and YZ ? respectively, where
? ? ,, X a b c ? , ? ? 1,2,3,4 Y ? and ? ? , Z ?? ? . Assume R1 and R2 can be
expressed as the following relation
1
0.2 0.6 0.8 0.9
0.5 0.1 0.6 0.4
0.7 0.3 0.2 0.7
R
??
??
?
??
??
??
and 2
0.6 0.2
0.3 0.7
0.4 0.9
0.8 0.5
R
??
??
??
?
??
??
??
Calculate the fuzzy max-min , and max- prod composition between two fuzzy
relations.
07
OR
(c)
Let
0.6 0.2 0.3 0.9
F
a b c d
??
? ? ? ?
??
??
be a fuzzy set. Find a set of ?-cut such that
F U F
?
?
? ? . How many such sets of ?-cuts are there? Justify your answer.
07
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Page 1 of 3
Seat No.: ________ Enrolment No.___________
GUJARAT TECHNOLOGICAL UNIVERSITY
BE - SEMESTER ? VII (New) EXAMINATION ? WINTER 2019
Subject Code: 2172009 Date: 30/11/2019
Subject Name: Soft Computing Applications
Time: 10:30 AM TO 01:00 PM Total Marks: 70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
Q.1 (a) Do as directed.
(i) State the difference between soft computing and hard computing with
reference to its problem solving capabilities.
(ii) With the suitable example define & explain the supervised and
unsupervised learning method.
03
(b) Identify the basic traits of soft computing as computational process and briefly
explain how any one of these traits help us in problem solving of engineering
sector.
04
(c) Explain the basic membership functions of fuzzy sets with a suitable example. 07
Q.2 (a) Consider two fuzzy sets A and B as shown
1 0.5 0.3 0.2
2 3 4 5
A
??
? ? ? ?
??
??
and
0.5 0.7 0.2 0.4
2 3 4 5
B
??
? ? ? ?
??
??
Calculate several operation on the fuzzy set (i) AB ? (ii) AB ? (iii) A (iv) B
(v) cardinality and relative cardinality of fuzzy sets A and B
03
(b)
For the fuzzy sets given in Q.2(a) find out
(i) Algebraic product (ii) Bounded sum (iii) Bounded difference
(iv) Algebraic sum
04
(c) Consider two fuzzy relations R1 and R2 on XY ? and YZ ? respectively, where
? ? ,, X a b c ? , ? ? 1,2,3,4 Y ? and ? ? , Z ?? ? . Assume R1 and R2 can be
expressed as the following relation
1
0.2 0.6 0.8 0.9
0.5 0.1 0.6 0.4
0.7 0.3 0.2 0.7
R
??
??
?
??
??
??
and 2
0.6 0.2
0.3 0.7
0.4 0.9
0.8 0.5
R
??
??
??
?
??
??
??
Calculate the fuzzy max-min , and max- prod composition between two fuzzy
relations.
07
OR
(c)
Let
0.6 0.2 0.3 0.9
F
a b c d
??
? ? ? ?
??
??
be a fuzzy set. Find a set of ?-cut such that
F U F
?
?
? ? . How many such sets of ?-cuts are there? Justify your answer.
07
Page 2 of 3
Q.3 (a) With suitable diagram explain the law of Excluded Middle and the law of
Contradiction.
03
(b) Define defuzzification and compare first of maxima and last of maxima method. 04
(c) For the logical union of the membership functions shown below Figure (a) and
(b), find the defuzzified value
*
x using centroid and weighted average method.
Figure (a) Figure (b)
07
OR
Q.3 (a) What is fuzzy equivalence relation? 03
(b) Define: reflexive and irreflexive properties of fuzzy relation. 04
(c) Figure shows three implication process results
1
C ,
2
C and
3
C . Find the aggregated
output and the defuzzified output using centroid method.
07
Q.4 (a) What is activation function? Explain the different types of activation functions
used in ANN?s.
03
(b) Sketch the Hebb network and show the steps of training algorithm for the same. 04
(c) Realize the Mc-Culloch-Pitts neuron model for AND gate (take binary data). 07
OR
Q.4 (a) Using McCulloch-Pitts neuron structure implement XOR function. (Consider
binary data).
03
(b) Explain the training algorithm of the Perceptron network. 04
(c) Classify the two-dimensional input pattern shown in figure using Perceptron
network. The symbol ?*? indicates the data representation to be +1 and ?#?
indicates data to be -1. For the pattern I, the target is +1 and for the pattern H,
the target is -1.
* * * * # *
# * # * * *
* * * * # *
Pattern ? I Pattern ? H
07
Q.5 (a) With the help of ADALINE network architecture, draw the flow diagram for the
step of learning in ADALINE network.
03
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Page 1 of 3
Seat No.: ________ Enrolment No.___________
GUJARAT TECHNOLOGICAL UNIVERSITY
BE - SEMESTER ? VII (New) EXAMINATION ? WINTER 2019
Subject Code: 2172009 Date: 30/11/2019
Subject Name: Soft Computing Applications
Time: 10:30 AM TO 01:00 PM Total Marks: 70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
Q.1 (a) Do as directed.
(i) State the difference between soft computing and hard computing with
reference to its problem solving capabilities.
(ii) With the suitable example define & explain the supervised and
unsupervised learning method.
03
(b) Identify the basic traits of soft computing as computational process and briefly
explain how any one of these traits help us in problem solving of engineering
sector.
04
(c) Explain the basic membership functions of fuzzy sets with a suitable example. 07
Q.2 (a) Consider two fuzzy sets A and B as shown
1 0.5 0.3 0.2
2 3 4 5
A
??
? ? ? ?
??
??
and
0.5 0.7 0.2 0.4
2 3 4 5
B
??
? ? ? ?
??
??
Calculate several operation on the fuzzy set (i) AB ? (ii) AB ? (iii) A (iv) B
(v) cardinality and relative cardinality of fuzzy sets A and B
03
(b)
For the fuzzy sets given in Q.2(a) find out
(i) Algebraic product (ii) Bounded sum (iii) Bounded difference
(iv) Algebraic sum
04
(c) Consider two fuzzy relations R1 and R2 on XY ? and YZ ? respectively, where
? ? ,, X a b c ? , ? ? 1,2,3,4 Y ? and ? ? , Z ?? ? . Assume R1 and R2 can be
expressed as the following relation
1
0.2 0.6 0.8 0.9
0.5 0.1 0.6 0.4
0.7 0.3 0.2 0.7
R
??
??
?
??
??
??
and 2
0.6 0.2
0.3 0.7
0.4 0.9
0.8 0.5
R
??
??
??
?
??
??
??
Calculate the fuzzy max-min , and max- prod composition between two fuzzy
relations.
07
OR
(c)
Let
0.6 0.2 0.3 0.9
F
a b c d
??
? ? ? ?
??
??
be a fuzzy set. Find a set of ?-cut such that
F U F
?
?
? ? . How many such sets of ?-cuts are there? Justify your answer.
07
Page 2 of 3
Q.3 (a) With suitable diagram explain the law of Excluded Middle and the law of
Contradiction.
03
(b) Define defuzzification and compare first of maxima and last of maxima method. 04
(c) For the logical union of the membership functions shown below Figure (a) and
(b), find the defuzzified value
*
x using centroid and weighted average method.
Figure (a) Figure (b)
07
OR
Q.3 (a) What is fuzzy equivalence relation? 03
(b) Define: reflexive and irreflexive properties of fuzzy relation. 04
(c) Figure shows three implication process results
1
C ,
2
C and
3
C . Find the aggregated
output and the defuzzified output using centroid method.
07
Q.4 (a) What is activation function? Explain the different types of activation functions
used in ANN?s.
03
(b) Sketch the Hebb network and show the steps of training algorithm for the same. 04
(c) Realize the Mc-Culloch-Pitts neuron model for AND gate (take binary data). 07
OR
Q.4 (a) Using McCulloch-Pitts neuron structure implement XOR function. (Consider
binary data).
03
(b) Explain the training algorithm of the Perceptron network. 04
(c) Classify the two-dimensional input pattern shown in figure using Perceptron
network. The symbol ?*? indicates the data representation to be +1 and ?#?
indicates data to be -1. For the pattern I, the target is +1 and for the pattern H,
the target is -1.
* * * * # *
# * # * * *
* * * * # *
Pattern ? I Pattern ? H
07
Q.5 (a) With the help of ADALINE network architecture, draw the flow diagram for the
step of learning in ADALINE network.
03
Page 3 of 3
(b) Write a short note on Adaptive Resonance Theory. 04
(c) With the help of block diagram and explain the application of neural network in
machine vision.
07
OR
Q.5 (a) State the merits and demerits of Kohonen Self-organizing feature maps. 03
(b) Write a short note on Learning Vector Quantization network. 04
(c) With the help of block diagram and flow chart, explain the application of fuzzy
logic in water level control.
07
**********
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This post was last modified on 20 February 2020