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Bit 4405 Expert Systems Question Paper
Bit 4405 Expert Systems
Course:Bachelor Of Science In Information Technology
Institution: Kca University question papers
Exam Year:2014
UNIVERSITY EXAMINATIONS: 2013/2014
ORDINARY EXAMINATION FOR THE BACHELOR OF SCIENCE
IN INFORMATION TECHNOLOGY
BIT 4405 EXPERT SYSTEMS
DATE: AUGUST, 2014
TIME: 2 HOURS
INSTRUCTIONS: Answer Question ONE and any other TWO
QUESTION ONE
a)
Discuss the situations in which backward chaining and forward chaining are
suitable for. (8 Marks)
b) Explain the genesis of post production system. (6 Marks)
c) Using examples differentiate between A priori knowledge and aposteriori
knowledge.
d)
(6 Marks)
Describe how the following classical rule bases systems are used in diagnosis of
bacterial infections and device configurations respectively
i) MYCIN (5 Marks)
ii) XCON (5 Marks)
QUESTION TWO
a)
Discuss the three axioms used in the formal theory of probability. (9 Marks)
b)
Use the following table to compute the probabilities below.
1. The probability of a crash for both Brand X and not Brand X
2. The probability of no crash for the sample space is
1
(7 Marks)
3. The probability of using Brand X is
4. The probability of not using Brand X is
5. The probability of a crash and using Brand X is
6. The probability of a crash, given that Brand X is used, is
7. The probability of a crash, given that Brand X is not used, is
c)
Using examples differentiate between exact reasoning and inexact reasoning
(4 Marks)
QUESTION THREE
a)
Consider the following MYCIN rule:
IF
1) The stain of the organism is gram positive, and
2) The morphology of the organism is coccus, and
3) The growth conformation of the organism is chains
THEN There is suggestive evidence (0.7) that the identity of the organism is
streptococcus in terms of posterior probability as:
Where the Ei correspond to the three patterns of the antecedent An expert would agree to
the above equation, they refuse to agree with the following probabilistic result:
Discuss why an expert may not agree with given results.
b)
(6 Marks)
Bayes’ Theorem’s accurate use depends on knowing many probabilities. The
probability to determine a specific disease given certain evidence is given by:
Where the sum over j extends to all diseases. Explain the various components of the
equation above.
(5 Marks)
2
Di is the i''th disease,
E is the evidence,
P(Di) is the prior probability of the patient having the Disease i before any evidence is
known
P(E | Di) is the conditional probability that the patient will exhibit evidence E, given that
disease Di is present
c)
Examine the three major participants in expert system development.
(9 Marks)
QUESTION FOUR
a) Differentiate between inference and explanation.
(4 Marks)
b) Describe the recognize-act cycles as facilitated by the inference engine.
(7 Marks)
c)
Discuss any three different areas of application of Bayesian system.
(9 Marks)
QUESTION FIVE
a)
Explain what an expert system is and explain the activities of transferring
expertise from an expert to a computer.
b)
Artificial intelligence is widely used in expert systems. Explain the features of a
good expert system.
c)
(6 Marks)
(8 Marks)
Explain the reasons that may encourage you to use expert systems. (6 Marks)
3
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