Download MU-(University of Mumbai or University of Bombay) 2019 May M.Sc IT Part II (Master of Science in Information Technology) 93697 Intelligent Systems and Neural Networks and Fuzzy Systems Previous Question Paper
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(Time: ?? hours)
[Total Marks: 75]
Please check that you have got the correct question paper.
N. B.: (1) All questions are compulsory.
(2) Make suitable assumptions wherever necessary and state the assumptions made.
(3) Answers to the same question must be written together.
(4) Numbers to the right indicate marks.
(5) Draw neat labeled diagrams wherever necessary.
(6) Use of Non-programmable calculators is allowed.
SECTION ? I
1.
a. What are intelligent systems? Explain 7
b. Write a short note on AI. Mention its applications. 6
OR
1.
a. Explain how utility-based agent is different than goal-based agent? Compare the
Characteristics of utility-based and goal-based agent.
7
b. Explain the structure of on intelligent system. 6
2.
a. What is UNIFICATION? Explain working of unification with examples. 7
b. State and explain the A* algorithm in brief. 6
OR
2.
a. State steps require converting every sentence of first order logic to equivalent CNF
sentence.
7
b. Write a note on Dempster-shafers belief networks theory. 6
3.
a. Describe Quantifiers with their uses. 6
b. Write a short note on Thinking Humanly ? a cognitive model approach. 6
OR
3.
a. Write a note on multi-layered feed forward network. 6
b. Compare the characteristics between prior probability and conditional probability. 6
Paper / Subject Code: 93697 / Information Technology : Paper III - Intelligent Systems and Neural Networks and Fuzzy Systems
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73242 Page 1 of 2
(Time: ?? hours)
[Total Marks: 75]
Please check that you have got the correct question paper.
N. B.: (1) All questions are compulsory.
(2) Make suitable assumptions wherever necessary and state the assumptions made.
(3) Answers to the same question must be written together.
(4) Numbers to the right indicate marks.
(5) Draw neat labeled diagrams wherever necessary.
(6) Use of Non-programmable calculators is allowed.
SECTION ? I
1.
a. What are intelligent systems? Explain 7
b. Write a short note on AI. Mention its applications. 6
OR
1.
a. Explain how utility-based agent is different than goal-based agent? Compare the
Characteristics of utility-based and goal-based agent.
7
b. Explain the structure of on intelligent system. 6
2.
a. What is UNIFICATION? Explain working of unification with examples. 7
b. State and explain the A* algorithm in brief. 6
OR
2.
a. State steps require converting every sentence of first order logic to equivalent CNF
sentence.
7
b. Write a note on Dempster-shafers belief networks theory. 6
3.
a. Describe Quantifiers with their uses. 6
b. Write a short note on Thinking Humanly ? a cognitive model approach. 6
OR
3.
a. Write a note on multi-layered feed forward network. 6
b. Compare the characteristics between prior probability and conditional probability. 6
Paper / Subject Code: 93697 / Information Technology : Paper III - Intelligent Systems and Neural Networks and Fuzzy Systems
86D0CC42D96BF93B0FBEE2A61D6597F7
86D0CC42D96BF93B0FBEE2A61D6597F786D0CC42D96BF93B0FBEE2A61D6597F786D0CC42D96BF93B0FBEE2A61D6597F786D0CC42D96BF93B0FBEE2A61D6597F786D0CC42D96BF93B0FBEE2A61D6597F786D0CC42D96BF93B0FBEE2A61D6597F7
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SECTION II
4.
a. Describe the McCulloch and Pitts models of neuron. 7
b. Write a note on ?Methods of steepest descend-LMS?. 6
OR
4.
a. Explain the least mean square algorithm. 7
b. Explain error correction learning. 6
5.
a. Explain the error correction mechanisms. 6
b. Explain Fuzzy Logic with one example. 6
OR
5.
a. What are MLP networks? How are they different from RBF Network? 6
b. State and explain Boltzmann learning mechanism. 6
6.
a. What is perceptron and mention perceptron convergence theorem. 6
b. Write a short note on membership functions in fuzzy logic. 6
OR
6. 6
a. Explain any 2 architectures of neural networks. 6
b. What are the salient features of Boltzmaan learning rule? Explain.
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Paper / Subject Code: 93697 / Information Technology : Paper III - Intelligent Systems and Neural Networks and Fuzzy Systems
86D0CC42D96BF93B0FBEE2A61D6597F7
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This post was last modified on 05 February 2020