Q.1
Fuzzy Inference Method Was Designed To Attempt What?
  • control any two combinations of any two products by synthesising a set of linguistic control rules obtained from experienced human operations.
  • control any two combinations of any two products by synthesising a set of linguistic control rules obtained from experienced human operations.
  • control a steam engine and a boiler combination by synthesising a set of linguistic control rules obtained from experienced human operations.
  • control a air craft and fuel level combination by synthesising a set of linguistic control rules obtained from experienced human operations.
Q.2
Fuzzy set wherein no membership function has its value equal to 1 is called
  • normal fuzzy set
  • subnormal fuzzy set.
  • convex fuzzy set
  • concave fuzzy set
Q.3
X is A and y is B then z=c (c is constant), is
  • rule in zero order fis
  • rule in first order fis
  • both a and b
  • neither a nor b
Q.4
Disjuctives antecedents is method of ----- in FLC
  • decomposition rule
  • formation of rule
  • truth tables
  • all of the above
Q.5
Conjuctives antecedents is method of ----- in FLC
  • decomposition rule
  • formation of rule
  • truth tables
  • all of the above
Q.6
Fuzzy propositions, ---- gives an approximate idea of the number of elements of a subset fulfilling certain conditions
  • fuzzy predicate and predicate modifiers
  • fuzzy quantifiers
  • fuzzy qualifiers
  • all of the above
Q.7
Defines logic funtion of two prepositions
  • prepositions
  • lingustic hedges
  • truth tables
  • inference rules
Q.8
Fuzzy set whose membership function has at least one element x in the universe whose membership valueis unity is called
  • sub normal fuzzy sets
  • normal fuzzy set
  • convex fuzzy set
  • concave fuzzy set
Q.9
Fuzzy logic and artificial neural network are soft computing techniques because
  • both gives precise an
  • ann gives accura
  • in each, no precise
  • fuzzy gives exact resul
Q.10
Equivalence between Fuzzy vs Probability to that of Prediction vs Forecasting is
  • fuzzy ≈ prediction
  • fuzzy ≈ forecastin
  • probability ≈ foreca
  • none of these
Q.11
The correct statementA fuzzy set is a crisp set but the reverse is not trueIf A,B and C are three fuzzy sets defined over the same universe of discourse such that A ≤ B and B ≤ C and A ≤ CMembership function defines the fuzziness in a fuzzy set irrespecive of the elements in the set, which are discrete or continuous
  • 1 only
  • 2 and 3
  • 1,2 and 3
  • none of these
Q.12
Fuzzy proposition "IF X is E then Y is F" is a
  • conditional unqualifi
  • unconditional unq
  • conditional qualifie
  • unconditional qualified
Q.13
A fuzzy set A defined on the interval X = [of integers by the membership JunctionμA(x) = x / (x+Then the α cut corresponding to α = 0.5 will be
  • {0, 1, 2, 3, 4, 5, 6, 7, 8
  • {1, 2, 3, 4, 5, 6, 7,
  • {2, 3, 4, 5, 6, 7, 8, 9,
  • none of the above
Q.14
U (B U C) =
  • (a ∩ b) ∩ (a ∩ c)
  • (a ∪ b ) ∪ c
  • (a ∪ b) ∩ (a ∪ c)
  • b ∩ a ∪ c
Q.15
The value of adding the following two fuzzy integers:A = {(0.3,1), (0.6,2), (1,3), (0.7,4), (0.2,5)} B = {(0.5,11), (1,12), (0.5,13)}Where fuzzy addition is defined asμA+B(z) = maxx+y=z (min(μA(x), μB(x))) Then, f(A+B) is equal to
  • {(0.5,12), (0.6,13), (1,
  • {(0.5,12), (0.6,13),
  • {(0.3,12), (0.5,13), (
  • {(0.3,12), (0.5,13), (0.6
Q.16
A and B are two fuzzy sets with membership functionsμA(x) = {0.0.0.0.0.8}μB(x) = {0.0.0.0.0.5}Then the value of μ(A∪B)’(x) will be
  • {0.9, 0.5, 0.6, 0.8, 0.8
  • {0.6, 0.2, 0.1, 0.7,
  • {0.1, 0.5, 0.4, 0.2, 0.
  • {0.1, 0.5, 0.4, 0.2, 0.3}
Q.17
U = {1,2,3,4,5,6,A = {(0.7), (1), (0.8)}then A will be: (where ~ → complement)
  • {(4, 0.7), (2,1), (1,0.8)
  • {(4, 0.3.): (5, 0), (6
  • {(l, 1), (2, 1), (3, 0.3)
  • {(3, 0.3), (6.0.2)}
Q.18
Values of the set membership is represented by
  • discrete set
  • degree of truth
  • probabilities
  • both degree of truth& probabilities
Q.19
What purpose Feedback neural networks are primarily used?
  • classification
  • feature mapping
  • pattern mapping
  • none of the mentioned
Q.20
In the neural networks can perform what kind of operations?
  • serial
  • parallel
  • serial or parallel
  • none of the mentioned
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