University Question with Answer

University Questions with Answers

Dec. 2013

Q.1 How to handle uncertain knowledge with example? (Refer section 7.1) [8]

Q.2 How to represent knowledge in an uncertain domain? (Refer section 7.1) [8]

Q.3 Explain the need of fuzzy set and fuzzy logic with example. (Refer section 7.4) [8]

May 2014

Q.4 Define uncertain knowledge, prior probability and conditional probability. State the Baye's theorem. How is it useful for decision making under uncertainty? Explain belief networks briefly. (Refer section 7.1)[6]

Q.5 What is a Bayesian network? How is the Bayesian network used in representing the uncertainty about knowledge? Explain the method of performing exact inference in won Bayesian networks. (Refer section 7.1) [10]

Q.6 Consider the following facts: (Refer section 7.2)

i) I saw my cat in the living room 3 hours ago.

ii) 2 hours ago my door blew open.

iii) Three quarters of the time my door blows open, my cat runs outside the door.

iv) One hour ago I thought I heard a cat noise in my living. Assume I was half certain.

v) In one hour period the probability that the cat will leave the room is 0.2. There is also a 0.2 probability that he may enter the room. What ts the certainty that the cat is in my living room? Use Bayesian networks to answer this.

[8]

Dec. 2014

Q.7 Explain variable elimination algorithm for answering queries on Bayesian networks. (Refer section 7.2)       [8]

Q.8 Discuss forward - backward algorithm in detail. (Refer section 7.5)[8]

May 2015

Q.9 Explain about the exact inference in Bayesian networks. (Refer section 7.2) [16]

Q.10 List down the applications of Bayesian network. (Refer section 7.1)[6]

Dec. 2016

Q.11 Explain the method of performing exact inference in Bayesian Networks. (Refer section 7.2)[16]

May 2017

Q.12 Explain about Dempster shafer theory. (Refer section 7.4)[16]

Dec. 2017

Q.13 Discuss about Bayesian theory and Bayesian network. (Refer section 7.1)

Q.14 Describe in details about Dampster-Shafer theory. (Refer section 7.4)

May 2018

Q.15 Discuss the need and structure of Bayesian networks. (Refer section 7.2) [13]