McqMate
1. 
When we say that the boundary is crisp 
A.  distinguish two regions clearly 
B.  cannot distinguish two regions clearly 
C.  collection of ordered pairs 
D.  none of these 
Answer» A. distinguish two regions clearly 
2. 
In computing the output is called as 
A.  consequent 
B.  outfeed 
C.  anticedents 
D.  premise 
Answer» A. consequent 
3. 
Fuzzy logic is a form of 
A.  two valued logic 
B.  crisp set logic 
C.  many value logic 
D.  binary set logic 
Answer» C. many value logic 
4. 
Control actions while computing should be 
A.  ambiguous 
B.  unambioguos 
C.  inaccurate 
D.  none of these 
Answer» B. unambioguos 
5. 
Core of soft computing is 
A.  fuzzy computing,neural computing,genetic algorithm 
B.  fuzzy network and artificial intelligence 
C.  neural science 
D.  genetic science 
Answer» A. fuzzy computing,neural computing,genetic algorithm 
6. 
Hard computing perfforms what type of computation 
A.  sequential 
B.  parallel 
C.  approxiamate 
D.  both a and b 
Answer» A. sequential 
7. 
Who iniated idea of sofft computing 
A.  charles darwin 
B.  rich and berg 
C.  mc culloch 
D.  lofti a zadeh 
Answer» D. lofti a zadeh 
8. 
Soft computing is based on 
A.  fuzzy logic 
B.  neural science 
C.  crisp software 
D.  binary logic 
Answer» A. fuzzy logic 
9. 
In soft computing the problems,algorithms can be 
A.  non adaptive 
B.  adaptive 
C.  static 
D.  all of the above 
Answer» B. adaptive 
10. 
Fuzzy Computing 
A.  mimics human behaviour 
B.  deals with inprecise,probablistic 
C.  exact information 
D.  both a and b 
Answer» D. both a and b 
11. 
Hard computing is also called as 
A.  evolutionary computing 
B.  conventional computing 
C.  non conventional computing 
D.  probablistic computing 
Answer» B. conventional computing 
12. 
Which computing produces accurate results 
A.  soft computing 
B.  hard computing 
C.  both a and b 
D.  none of the above 
Answer» B. hard computing 
13. 
Neural network computing 
A.  mimics human behaviour 
B.  information processing paradigm 
C.  both a and b 
D.  none of the above 
Answer» C. both a and b 
14. 
Artificial neural network is used for 
A.  pattern recognition 
B.  classification 
C.  clustering 
D.  all of the above 
Answer» D. all of the above 
15. 
How does blind search differ from optimization 
A.  blind search represent a guided approach while optimization is unguided 
B.  blind search usually does not conclude in one step like some optimization methods. 
C.  blind search cannot result in optimal solution whereas optimization method do 
D.  none of these 
Answer» B. blind search usually does not conclude in one step like some optimization methods. 
16. 
In modeling,an optimal solution is understood to be 
A.  a solution that can only be determined by an exhaustive enumeration testing of alternatives 
B.  a solution found in the least possible time and using the least possible computing resources 
C.  a solution that is the best based on criteria defined in the design phase 
D.  a solution that requires an algorithm for the determination 
Answer» C. a solution that is the best based on criteria defined in the design phase 
17. 
When is a complete enumeration of solution used? 
A.  when a solution that is "good enough" is fine and good heuristics are available 
B.  when there is enough time and computational power available 
C.  when the modeler requires a guided approach to problem solving 
D.  when there are an infinite number of solution to be searched 
Answer» B. when there is enough time and computational power available 
18. 
All of the follwing are true about heuristics EXCEPT 
A.  heuristics are used when the modeler requires a guided approach to problem solving 
B.  heuristics are used when a solution that is "good enough" is sought 
C.  heuristics are used when there is abundant time and computational power 
D.  heuristics are rules of good judgement 
Answer» C. heuristics are used when there is abundant time and computational power 
19. 
Which approach is most suited to structured problem with little uncertainity 
A.  simuation 
B.  human intuition 
C.  optimization 
D.  genetic algorithm 
Answer» C. optimization 
20. 
Genetic algorithm belong to the family of method in the 
A.  artifical intelligence area 
B.  optimization area 
C.  complete enumeration family of methods 
D.  non computer based isolation area 
Answer» A. artifical intelligence area 
21. 
What does the 0 membership value means in the set 
A.  the object is fully inside the set 
B.  the object is not in the set 
C.  the object is partially present in the set 
D.  none of the above 
Answer» B. the object is not in the set 
22. 
The union of two fuzzy sets is the_______of each element from two sets 
A.  maximum 
B.  minimum 
C.  equal to 
D.  not equal to 
Answer» A. maximum 
23. 
The process of fuzzy interference system involes 
A.  membership functions 
B.  fuzzy logic operators 
C.  ifthen rules 
D.  all the above 
Answer» D. all the above 
24. 
What does a fuzzifier do 
A.  coverts crisp input to linguistic variables 
B.  coverts crisp ouput to linguistic variables 
C.  coverts fuzzy input to linguistic variables 
D.  coverts fuzzy output to linguistic variables 
Answer» A. coverts crisp input to linguistic variables 
25. 
Which of the folloowing is not defuzzifier method 
A.  centroid of area 
B.  mean of maximum 
C.  largest of maximum 
D.  hypotenuse of triangle 
Answer» D. hypotenuse of triangle 
26. 
Which of the following is/are type of fuzzy interference method 
A.  mamdani 
B.  sugeno 
C.  rivest 
D.  only a and b 
Answer» D. only a and b 
27. 
A Fuzzy rule can have 
A.  multiple part of antecedent,only single part of consequent 
B.  only single part of antecedent,mutiple part of consequent 
C.  multiple part of antecedent,multiple part of consequent 
D.  only single part of antecedent,only single part of consequent 
Answer» C. multiple part of antecedent,multiple part of consequent 
28. 
The a cut of a fuzzy set A is a crisp set defined by : 
A.  {xua(x)>a} 
B.  {xua(x)>=a} 
C.  {xua(x)<a} 
D.  {xua(x)<=a} 
Answer» B. {xua(x)>=a} 
29. 
The bandwidth(A) in a fuzzy set is given by 
A.  (a)=x1*x2 
B.  (a)=x1+x2 
C.  (a)=x1x2 
D.  (a)=x1/x2 
Answer» C. (a)=x1x2 
30. 
The intersection of two fuzzy sets is the_______of each element from two sets 
A.  maximum 
B.  minimum 
C.  equal to 
D.  not equal to 
Answer» B. minimum 
31. 
A={1/a,0.3/b,0.2/c,0.8/d,0/e} B={0.6/a,0.9/b,0.1/c,0.3/d,0.2/e} What will be the complement of A? 
A.  {0/a,0.7/b,0.8/c,0.2/d,1/e} 
B.  {0/a,0.9/b,0.7/c,0.2/d,1/e} 
C.  {0.8/a,0.7/b,0.8/c,0.7/d,1/e} 
D.  {0/a,0.7/b,0.8/c,0.9/d,1/e} 
Answer» A. {0/a,0.7/b,0.8/c,0.2/d,1/e} 
32. 
A={1/a,0.3/b,0.2/c,0.8/d,0/e} B={0.6/a,0.9/b,0.1/c,0.3/d,0.2/e} What will be the union of AUB? 
A.  {1/a,0.9/b,0.1/c,0.5/d,0.2/e} 
B.  {0.8/a,0.9/b,0.2/c,0.5/d,0.2/e} 
C.  {1/a,0.9/b,0.2/c,0.8/d,0.2/e} 
D.  {1/a,0.9/b,0.2/c,0.8/d,0.8/e} 
Answer» C. {1/a,0.9/b,0.2/c,0.8/d,0.2/e} 
33. 
A={1/a,0.3/b,0.2/c,0.8/d,0/e} B={0.6/a,0.9/b,0.1/c,0.3/d,0.2/e} What will be the intersection of A and B ? 
A.  {0.6/a,0.3/b,0.1/c,0.3/d,0/e} 
B.  {0.6/a,0.8/b,0.1/c,0.3/d,0/e} 
C.  {0.6/a,0.3/b,0.1/c,0.5/d,0/e} 
D.  {0.6/a,0.3/b,0.2/c,0.3/d,1/e} 
Answer» A. {0.6/a,0.3/b,0.1/c,0.3/d,0/e} 
34. 
What denotes the support(A) in a fuzzy set? 
A.  {xua(x)>0} 
B.  {xua(x)<0} 
C.  {xua(x)<=0} 
D.  {xua(x)<0.5} 
Answer» A. {xua(x)>0} 
35. 
What denotes the core(A) in a fuzzy set? 
A.  {xua(x)>0} 
B.  {xua(x)=1} 
C.  {xua(x)>=0.5} 
D.  {xua(x)>0.8} 
Answer» B. {xua(x)=1} 
36. 
Fuzzy logic deals with which of the following 
A.  fuzzy set 
B.  fuzzy algebra 
C.  both a and b 
D.  none of the above 
Answer» C. both a and b 
37. 
which of the following is a sequence of steps taken in designning a fuzy logic machine 
A.  fuzzification>rule evaluation>deffuzification 
B.  deffuzification>rule evaluation>fuzzification 
C.  rule evaluation>fuzzification>deffuzification 
D.  rule evaluation>defuzzification>fuzzification 
Answer» A. fuzzification>rule evaluation>deffuzification 
38. 
can a crisp set be a fuzzy set? 
A.  no 
B.  yes 
C.  depends 
D.  all of the above 
Answer» B. yes 
39. 
All of the follwing are suitable problem for genetic algorithm EXCEPT 
A.  pattern recognization 
B.  simulation of biological models 
C.  simple optimization with few variables 
D.  dynamic process control 
Answer» C. simple optimization with few variables 
40. 
Tabu search is an example of ? 
A.  heuristic 
B.  evolutionary algorithm 
C.  aco 
D.  pso 
Answer» A. heuristic 
41. 
Genetic algorithms are example of 
A.  heuristic 
B.  evolutionary algorithm 
C.  aco 
D.  pso 
Answer» B. evolutionary algorithm 
42. 
mutation is applied on __candidates. 
A.  one 
B.  two 
C.  more than two 
D.  noneof these 
Answer» A. one 
43. 
recombination is applied on __candidates. 
A.  one 
B.  two 
C.  more than two 
D.  noneof these 
Answer» B. two 
44. 
LCS belongs to ___ based methods? 
A.  rule based learning 
B.  genetic learning 
C.  both a and b 
D.  noneof these 
Answer» A. rule based learning 
45. 
Survival is ___ approach. 
A.  deteministic 
B.  non deterministic 
C.  semi deterministic 
D.  noneof these 
Answer» A. deteministic 
46. 
Evolutionary algorithms are a ___ based approach 
A.  heuristic 
B.  metaheuristic 
C.  both a and b 
D.  noneof these 
Answer» A. heuristic 
47. 
Idea of genetic algorithm came from 
A.  machines 
B.  birds 
C.  aco 
D.  genetics 
Answer» D. genetics 
48. 
Chromosomes are actually ? 
A.  line representation 
B.  string representation 
C.  circular representation 
D.  all of these 
Answer» B. string representation 
49. 
what are the parameters that affect GA are/is 
A.  selection process 
B.  initial population 
C.  both a and b 
D.  none of these 
Answer» C. both a and b 
50. 
Evolutionary programming was developef by 
A.  fredrik 
B.  fodgel 
C.  frank 
D.  flin 
Answer» B. fodgel 
51. 
Evolution Strategies is developed with 
A.  selection 
B.  mutation 
C.  a population of size one 
D.  all of these 
Answer» D. all of these 
52. 
Evolution Strategies typically uses 
A.  realvalued vector representations 
B.  vector representation 
C.  time based representation 
D.  none of these 
Answer» A. realvalued vector representations 
53. 
in ES survival is 
A.  indeterministic 
B.  deterministic 
C.  both a and b 
D.  none of these 
Answer» D. none of these 
54. 
What is the first step in Evolutionary algorithm 
A.  termination 
B.  selection 
C.  recombination 
D.  initialization 
Answer» D. initialization 
55. 
Elements of ES are/is 
A.  parent population size 
B.  survival population size 
C.  both a and b 
D.  none of these 
Answer» C. both a and b 
56. 
What are different types of crossover 
A.  discrete and intermedium 
B.  discrete and continuous 
C.  continuous and intemedium 
D.  none of these 
Answer» A. discrete and intermedium 
57. 
Determining the duration of the simulation occurs before the model is validated and tested. 
A.  true 
B.  false 
Answer» B. false 
58. 
_________cannot easily be transferred from one problem domain to another 
A.  optimal solution 
B.  analytical solution 
C.  simulation solutuon 
D.  none of these 
Answer» C. simulation solutuon 
59. 
Discrete events and agentbased models are usuallly used for_____________. 
A.  middle or low level of abstractions 
B.  high level of abstraction 
C.  very high level of abstraction 
D.  none of these 
Answer» A. middle or low level of abstractions 
60. 
_____doesnot usually allow decision makers to see how a solution to a ___________envolves over time nor can decision makers interact with it. 
A.  simulation ,complex problem 
B.  simulation,easy problem 
C.  genetics,complex problem 
D.  genetics,easy problem 
Answer» A. simulation ,complex problem 
61. 
EC stands for? 
A.  evolutionary computatons 
B.  evolutionary computer 
C.  electronic computations 
D.  noneof these 
Answer» A. evolutionary computatons 
62. 
GA stands for 
A.  genetic algorithm 
B.  genetic asssurance 
C.  genese alforithm 
D.  noneof these 
Answer» A. genetic algorithm 
63. 
LCS stands for 
A.  learning classes system 
B.  learning classifier systems 
C.  learned class system 
D.  noneof these 
Answer» B. learning classifier systems 
64. 
GBML stands for 
A.  genese based machine learning 
B.  genes based mobile learning 
C.  genetic bsed machine learning 
D.  noneof these 
Answer» C. genetic bsed machine learning 
65. 
EV is dominantly used for solving ___. 
A.  optimization problems 
B.  np problem 
C.  simple problems 
D.  noneof these 
Answer» A. optimization problems 
66. 
EV is considered as? 
A.  adaptive 
B.  complex 
C.  both a and b 
D.  noneof these 
Answer» C. both a and b 
67. 
Parameters that affect GA 
A.  initial population 
B.  selection process 
C.  fitness function 
D.  all of these 
Answer» D. all of these 
68. 
Fitness function should be 
A.  maximum 
B.  minimum 
C.  intermediate 
D.  noneof these 
Answer» B. minimum 
69. 
Applying recombination and mutation leads to a set of new candidates, called as ? 
A.  sub parents 
B.  parents 
C.  offsprings 
D.  grand child 
Answer» C. offsprings 
70. 
____ decides who becomes parents and how many children the parents have. 
A.  parent combination 
B.  parent selection 
C.  parent mutation 
D.  parent replace 
Answer» B. parent selection 
71. 
Basic elements of EA are ? 
A.  parent selection methods 
B.  survival selection methods 
C.  both a and b 
D.  noneof these 
Answer» C. both a and b 
72. 
There are also other operators, more linguistic in nature, called __________ that can be applied to fuzzy set theory. 
A.  hedges 
B.  lingual variable 
C.  fuzz variable 
D.  none of the mentioned 
Answer» A. hedges 
73. 
A fuzzy set has a membership function whose membership values are strictly monotonically increasing or strictly monotonically decreasing or strictly monotonically increasing than strictly monotonically decreasing with increasing values for elements in the universe 
A.  convex fuzzy set 
B.  concave fuzzy set 
C.  non concave fuzzy set 
D.  non convex fuzzy set 
Answer» A. convex fuzzy set 
74. 
Which of the following neural networks uses supervised learning?

A.  (a) only 
B.  (b) only 
C.  (a) and (b) only 
D.  (a) and (c) only 
Answer» A. (a) only 
75. 
What is the feature of ANNs due to which they can deal with noisy, fuzzy, inconsistent data? 
A.  associative nature of networks 
B.  distributive nature of networks 
C.  both associative & distributive 
D.  none of the mentioned 
Answer» C. both associative & distributive 
76. 
Feature of ANN in which ANN creates its own organization or representation of information it receives during learning time is 
A.  adaptive learning 
B.  self organization 
C.  whatif analysis 
D.  supervised learning 
Answer» B. self organization 
77. 
Any softcomputing methodology is characterised by 
A.  precise solution 
B.  control actions are unambiguous and accurate 
C.  control actions is formally defined 
D.  algorithm which can easily adapt with the change of dynamic environment 
Answer» D. algorithm which can easily adapt with the change of dynamic environment 
78. 
For what purpose Feedback neural networks are primarily used? 
A.  classification 
B.  feature mapping 
C.  pattern mapping 
D.  none of the mentioned 
Answer» D. none of the mentioned 
79. 
Operations in the neural networks can perform what kind of operations? 
A.  serial 
B.  parallel 
C.  serial or parallel 
D.  none of the mentioned 
Answer» C. serial or parallel 
80. 
What is ART in neural networks? 
A.  automatic resonance theory 
B.  artificial resonance theory 
C.  adaptive resonance theory 
D.  none of the mentioned 
Answer» C. adaptive resonance theory 
81. 
The values of the set membership is represented by ___________ 
A.  discrete set 
B.  degree of truth 
C.  probabilities 
D.  both degree of truth & probabilities 
Answer» B. degree of truth 
82. 
Given U = {1,2,3,4,5,6,7}

A.  {(4, 0.7), (2,1), (1,0.8)} 
B.  {(4, 0.3.): (5, 0), (6. 0.2) } 
C.  {(l, 1), (2, 1), (3, 0.3), (4, 1), (6,0.2), (7, 1)} 
D.  {(3, 0.3), (6.0.2)} 
Answer» C. {(l, 1), (2, 1), (3, 0.3), (4, 1), (6,0.2), (7, 1)} 
83. 
What are the following sequence of steps taken in designing a fuzzy logic machine ? 
A.  fuzzification → rule evaluation → defuzzification 
B.  fuzzification → defuzzification → rule evaluation 
C.  rule evaluation → fuzzification → defuzzification 
D.  rule evaluation → defuzzification → fuzzification 
Answer» A. fuzzification → rule evaluation → defuzzification 
84. 
If A and B are two fuzzy sets with membership functions

A.  {0.9, 0.5, 0.6, 0.8, 0.8} 
B.  {0.6, 0.2, 0.1, 0.7, 0.5} 
C.  {0.1, 0.5, 0.4, 0.2, 0.2} 
D.  {0.1, 0.5, 0.4, 0.2, 0.3} 
Answer» C. {0.1, 0.5, 0.4, 0.2, 0.2} 
85. 
Compute the value of adding the following two fuzzy integers:

A.  {(0.5,12), (0.6,13), (1,14), (0.7,15), (0.7,16), (1,17), (1,18)} 
B.  {(0.5,12), (0.6,13), (1,14), (1,15), (1,16), (1,17), (1,18)} 
C.  {(0.3,12), (0.5,13), (0.5,14), (1,15), (0.7,16), (0.5,17), (0.2,18)} 
D.  {(0.3,12), (0.5,13), (0.6,14), (1,15), (0.7,16), (0.5,17), (0.2,18)} 
Answer» D. {(0.3,12), (0.5,13), (0.6,14), (1,15), (0.7,16), (0.5,17), (0.2,18)} 
86. 
A U (B U C) = 
A.  (a ∩ b) ∩ (a ∩ c) 
B.  (a ∪ b ) ∪ c 
C.  (a ∪ b) ∩ (a ∪ c) 
D.  b ∩ a ∪ c 
Answer» B. (a ∪ b ) ∪ c 
87. 
Consider a fuzzy set A defined on the interval X = [0, 10] of integers by the membership Junction

A.  {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10} 
B.  {1, 2, 3, 4, 5, 6, 7, 8, 9, 10} 
C.  {2, 3, 4, 5, 6, 7, 8, 9, 10} 
D.  none of the above 
Answer» C. {2, 3, 4, 5, 6, 7, 8, 9, 10} 
88. 
The fuzzy proposition "IF X is E then Y is F" is a 
A.  conditional unqualified proposition 
B.  unconditional unqualified proposition 
C.  conditional qualified proposition 
D.  unconditional qualified proposition 
Answer» A. conditional unqualified proposition 
89. 
Choose the correct statement

A.  1 only 
B.  2 and 3 
C.  1,2 and 3 
D.  none of these 
Answer» B. 2 and 3 
90. 
An equivalence between Fuzzy vs Probability to that of Prediction vs Forecasting is 
A.  fuzzy ≈ prediction 
B.  fuzzy ≈ forecasting 
C.  probability ≈ forecasting 
D.  none of these 
Answer» B. fuzzy ≈ forecasting 
91. 
Both fuzzy logic and artificial neural network are soft computing techniques because 
A.  both gives precise and accurate result 
B.  ann gives accurate result, but fuzzy logic does not 
C.  in each, no precise mathematical model of problem is acquired 
D.  fuzzy gives exact result but ann does not 
Answer» C. in each, no precise mathematical model of problem is acquired 
92. 
A fuzzy set whose membership function has at least one element x in the universe whose membership value is unity is called 
A.  sub normal fuzzy sets 
B.  normal fuzzy set 
C.  convex fuzzy set 
D.  concave fuzzy set 
Answer» B. normal fuzzy set 
93. 
 defines logic funtion of two prepositions 
A.  prepositions 
B.  lingustic hedges 
C.  truth tables 
D.  inference rules 
Answer» C. truth tables 
94. 
In fuzzy propositions,  gives an approximate idea of the number of elements of a subset fulfilling certain conditions 
A.  fuzzy predicate and predicate modifiers 
B.  fuzzy quantifiers 
C.  fuzzy qualifiers 
D.  all of the above 
Answer» B. fuzzy quantifiers 
95. 
Multiple conjuctives antecedents is method of  in FLC 
A.  decomposition rule 
B.  formation of rule 
C.  truth tables 
D.  all of the above 
Answer» A. decomposition rule 
96. 
Multiple disjuctives antecedents is method of  in FLC 
A.  decomposition rule 
B.  formation of rule 
C.  truth tables 
D.  all of the above 
Answer» A. decomposition rule 
97. 
IF x is A and y is B then z=c (c is constant), is 
A.  rule in zero order fis 
B.  rule in first order fis 
C.  both a and b 
D.  neither a nor b 
Answer» A. rule in zero order fis 
98. 
A fuzzy set wherein no membership function has its value equal to 1 is called 
A.  normal fuzzy set 
B.  subnormal fuzzy set. 
C.  convex fuzzy set 
D.  concave fuzzy set 
Answer» B. subnormal fuzzy set. 
99. 
Mamdani's Fuzzy Inference Method Was Designed To Attempt What? 
A.  control any two combinations of any two products by synthesising a set of linguistic control rules obtained from experienced human operations. 
B.  control any two combinations of any two products by synthesising a set of linguistic control rules obtained from experienced human operations. 
C.  control a steam engine and a boiler combination by synthesising a set of linguistic control rules obtained from experienced human operations. 
D.  control a air craft and fuel level combination by synthesising a set of linguistic control rules obtained from experienced human operations. 
Answer» C. control a steam engine and a boiler combination by synthesising a set of linguistic control rules obtained from experienced human operations. 
100. 
What Are The Two Types Of Fuzzy Inference Systems? 
A.  modeltype and systemtype 
B.  momfredtype and semigitype 
C.  mamdanitype and sugenotype 
D.  mihnitype and sujganitype 
Answer» C. mamdanitype and sugenotype 
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