LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034
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M.Sc. DEGREE EXAMINATION – STATISTICS
THIRD SEMESTER – April 2009
ST 3875 – FUZZY THEORY AND APPLICATIONS
Date & Time: 27/04/2009 / 9:00 – 12:00 Dept. No. Max. : 100 Marks
SECTION – A |
Answer ALL the Questions (10 x 2 = 20 marks)
- Write the axiomatic skeleton of fuzzy t-conorm.
- Define Archimedean t-norm.
- Define Drastic fuzzy intersection.
- Write a short note on fuzzy number.
- If , find
- Define a fuzzy variable and give an example.
- Define scalar cardinality of a fuzzy set.
- State the role of a ‘knowledge engineer’ in constructing fuzzy sets.
- Distinguish between direct methods and indirect methods of constructing membership functions.
- Define an artificial neural network.
SECTION – B |
Answer any FIVE Questions (5 x 8 = 40 marks)
- Define & and prove that ,.
- Prove that , where and denote drastic and yager class of t-norm.
- Let the triple be a dual generated by an increasing generator. Prove that fuzzy operations satisfy the law of excluded middle and the law of contradiction. Also prove that does not satisfy distributive law.
- Let and B. Find the 4 basic operations for the fuzzy numbers A and B.
- Prove under usual notations: (i) α(Ac) = ( (1 – α) +A)c (ii) = α+ ()
- State the axiomatic skeleton and desirable requirements for fuzzy complements. Prove that if the monotonic and involutive axioms are satisfied, then the boundary and continuity conditions are satisfied.
- Let X ={x1, x2 ,x3} be a universal set and suppose two experts E1 and E2 have specified the valuations of these three as elements of two fuzzy sets A and B as
given in the following table:
Membership in A Membership in B
Element | E1 | E2 |
x1 | 0.6 | 0.5 |
x2 | 0.2 | 0.3 |
x3 | 0.8 | 0.6 |
Element | E1 | E2 |
x1 | 0.2 | 0.4 |
x2 | 0.9 | 0.7 |
x3 | 0.6 | 0.3 |
Assuming that for set A, the experts have to be given weights as c1 = 0.7 and c2 = 0.3 and that for set B, the weights are c1 = 0.2, c2 = 0.8, find the degree of membership of the three elements in A and in B. Also, find the degree of membership in AUB by bounded sum operator.
- State the three different classes of network architectures and briefly describe any one of them with a diagram.
SECTION -C |
Answer any TWO Questions (2 x 20 = 40 marks)
- (a) Let i be a t-norm and strictly increasing and continuous function in (0,1) such that g(0)=0, g(1)=1. Prove that the function , where denotes pseudo inverse of g is a t-norm.
(b) Prove that the triples and are dual with
respect to any fuzzy complement. (15+5)
- Let MIN and MAX be binary operations on the set of all fuzzy numbers. Prove that for any fuzzy numbers A, B, C the following properties hold:
(a) MIN(A,MIN(B,C))=MIN(MIN(A,B),C)
(b) MAX(A,MAX(B,C))=MAX(MAX(A,B),C)
(c) MIN(A,MAX(A,B))=A
(d) MAX(A,MIN(A,B))=A
(e) MIN(A,MAX(B,C))=MAX(MIN(A,B), MIN(A,C))
(f) MAX(A,MIN(B,C))=MIN(MAX(A,B), MAX(A,C))
- (a)Explain the indirect method of constructing a membership function with one expert.
(b) State the role of ‘activation function’ in neural networks. Describe the three basic types of activation functions. (10 + 10)
- (a) Briefly explain the three practical issues in ‘Pattern Recognition’.
(b) State the problem of ‘Fuzzy Clustering’ and present the Fuzzy c-means
algorithm. (6 + 14)