Soft Computing mcq pdf for SPPU online exam

Q. 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

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Distinguish two regions clearly

Q. In computing the output is called as
A: Consequent
B: Outfeed
C: Anticedents
D: Premise

Consequent

Q. Fuzzy logic is a form of
A: two valued logic
B: crisp set logic
C: many value logic
D: binary set logic
c

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many value logic

Q. Control actions while computing should be
A: Ambiguous
B: Unambioguos
C: Inaccurate
D: None of these

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Unambioguos

Q. Core of soft computing is
A: Fuzzy computing,neural computing,Genetic algorithm
B: Fuzzy network and artificial intelligence
C: Neural Science
D: Genetic Science

Fuzzy computing,neural computing,Genetic algorithm

Q. Hard computing performs what type of computation
A: Sequential
B: Parallel
C: approxiamate
D: both a and b

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Sequential

Q. Who iniated idea of soft computing
A: charles darwin
B: rich and berg
C: mc culloch
D: lofti a zadeh

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lofti a zadeh

Q. Soft computing is based on
A: fuzzy logic
B: neural science
C: crisp software
D: binary logic

fuzzy logic

Q. In soft computing the problems,algorithms can be
A: non adaptive
B: adaptive
C: static
D: all of the above

adaptive

Q. Fuzzy Computing
A: mimics human behaviour
B: deals with inprecise,probablistic
C: exact information
D: both a and b

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both a and b

Q. Hard computing is also called as
A: evolutionary computing
B: conventional computing
C: non conventional computing
D: probablistic computing

conventional computing

Q. Which computing produces accurate results
A: soft computing
B: hard computing
C: both a and b
D: none of the above

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hard computing

Q. Neural network computing
A: mimics human behaviour
B: information processing paradigm
C: both a and b
D: none of the above

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both a and b

Q. Artificial neural network is used for
A: pattern recognition
B: classification
C: clustering
D: all of the above

all of the above

Q. 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

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Blind search usually does not conclude in one step like some optimization methods.

Q. 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

a solution that is the best based on criteria defined in the design phase

Q. 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

When there is enough time and computational power available

Q. 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

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heuristics are used when there is abundant time and computational power

Q. Which approach is most suited to structured problem with little uncertainity
A: Simuation
B: human intuition
C: Optimization
D: genetic algorithm

Optimization

Q. 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

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artifical intelligence area

Q. 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

the object is not in the set

Q. 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

maximum

Q. The process of fuzzy interference system involes
A: membership functions
B: fuzzy logic operators
C: if-then rules
D: all the above
d

all the above

Q. 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

coverts crisp input to linguistic variables

Q. Which of the following is not defuzzifier method
A: centroid of area
B: mean of maximum
C: largest of maximum
D: hypotenuse of triangle

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hypotenuse of triangle

Q. Which of the following is/are type of fuzzy interference method
A: mamdani
B: sugeno
C: rivest
D: only a and b

only a and b

Q. 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

multiple part of antecedent,multiple part of consequent

Q.The a cut of a fuzzy set A is a crisp set defined by :-
A: {x|Ua(x)>a}
B: {x|Ua(x)>=a}
C: {x|Ua(x)

{x|Ua(x)>=a}

Q.The bandwidth(A) in a fuzzy set is given by
A: (A)=|x1*x2|
B: (A)=|x1+x2|
C: (A)=|x1-x2|
D: (A)=|x1/x2|

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(A)=|x1-x2|

Q.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

minimum

Q. 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}

{0/a,0.7/b,0.8/c,0.2/d,1/e}

Q. 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}

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{1/a,0.9/b,0.2/c,0.8/d,0.2/e}

Q. 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}

{0.6/a,0.3/b,0.1/c,0.3/d,0/e}

Q. What denotes the support(A) in a fuzzy set?
A: {x|Ua(x)>0}
B: {x|Ua(x)<0}
C: {x|Ua(x)<=0}
D: {x|Ua(x)<0.5}

{x|Ua(x)>0}

Q. What denotes the core(A) in a fuzzy set?
A: {x|Ua(x)>0}
B: {x|Ua(x)=1}
C: {x|Ua(x)>=0.5}
D: {x|Ua(x)>0.8}

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{x|Ua(x)=1}

Q. Fuzzy logic deals with which of the following
A: fuzzy set
B: fuzzy algebra
C: both a and b
D: none of the above

both a and b

Q. 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

fuzzification->Rule Evaluation->Deffuzification

Q. can a crisp set be a fuzzy set?
A: no
B: yes
C: depends
D: all of the above

yes

Q. 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

artifical intelligence area

Q. 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

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simple optimization with few variables

Q. Genetic algorithms are example of
A: heuristic
B: Evolutionary algorithm
C: ACO
D: PSO

Evolutionary algorithm

Q. mutation is applied on __candidates.
A: one
B: two
C: more than two
D: noneof these

one

Q. recombination is applied on __candidates.
A: one
B: two
C: more than two
D: none of these

two

Q. LCS belongs to ___ based methods?
A: rule based learning
B: genetic learning
C: both a and b
D: none of these

rule based learning

Q. Survival is ___ approach.
A: deteministic
B: non deterministic
C: semi deterministic
D: none of these

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deteministic

Q. Evolutionary algorithms are a ___ based approach
A: heuristic
B: metaheuristic
C: both a and b
D: noneof these

heuristic

Q. Tabu search is an example of ?
A: heuristic
B: Evolutionary algorithm
C: ACO
D: PSO

heuristic

Q. Idea of genetic algorithm came from
A: machines
B: Birds
C: ACO
D: genetics

genetics

Q. Chromosomes are actually ?
A: line representation
B: String representation
C: Circular representation
D: all of these

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String representation

Q. what are the parameters that affect GA are/is
A: selection process
B: initial population
C: both a and b
D: none of these

both a and b

Q. Evolutionary programming was developed by
A: Fredrik
B: Fodgel
C: Frank
D: Flin

Fodgel

Q. Evolution Strategies is developed with
A: selection
B: mutation
C: a population of size one
D: all of these

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all of these

Q. Evolution Strategies typically uses
A: real-valued vector representations
B: vector representation
C: time based representation
D: none of these

real-valued vector representations

Q. in ES survival is
A: indeterministic
B: deterministic
C: both a and b
D: none of these

none of these

Q. What is the first step in Evolutionary algorithm
A: Termination
B: selection
C: Recombination
D: Initialization

Initialization

Q. Elements of ES are/is
A: Parent population size
B: Survival population size
C: both a and b
D: none of these

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both a and b

Q. What are different types of crossover
A: discrete and intermedium
B: discrete and continuous
C: continuous and intemedium
D: none of these

discrete and intermedium

Q. _________cannot easily be transferred from one problem domain to another
A: optimal solution
B: analytical solution
C: simulation solution
D: none of these

simulation solution

Q. Discrete events and agent based 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

middle or low level of abstractions

Q. _____does not 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

Simulation ,Complex problem

Q. EC stands for?
A: Evolutionary Computatons
B: Evolutionary computer
C: Electronic computations
D: none of these

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Evolutionary Computatons

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