cannot easily be transferred from one problem domain to another
1.optimal solution
2.analytical solution
3.simulation solutuon
4.none of these
decides who becomes parents and how many children the parents have.
1.parent combination
2.parent selection
3.parent mutation
4.parent replace
doesnot usually allow decision makers to see how a solution to a en
1.simulation ,complex
2.simulation,easy p
3.genetics,complex p
4.genetics,easy problem
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 uni1.{1/a,0.9/b,0.1/c,0.5/
2.{0.8/a,0.9/b,0.2/c
3. {1/a,0.9/b,0.2/c,0.8
4.{1/a,0.9/b,0.2/c,0.8/d,
Discrete events and agent-based models are usuallly used for .
1.middle or low level o
2.high level of abstr
3. very high level of ab
4.none of these
EV is considered as?
1. adaptive
2.complex
3.both a and b
4.noneof these
Fitness function should be
1.maximum
2.minimum
3.intermediate
4. noneof these
Fuzzy Computing
1.mimics human behav
2. deals with inpreci
3. exact information
4.both a and b
Genetic algorithms are example of
1.heuristic
2.evolutionary algo
3.aco
4.pso
Idea of genetic algorithm came from
1.machines
2.birds
3.aco
4.genetics
In computing the output is called as
1.consequent
2.outfeed
3.anticedents
4.premise
LCS stands for
1. learning classes syste
2. learning classifier
3. learned class syste
4.mnoneof these
Tabu search is an example of ?
1.heuristic
2.evolutionary algo
3.aco
4. pso
The a cut of a fuzzy set A is a crisp set defined by :-
1.{x|ua(x)>a}
2. {x|ua(x)>=a}
3.{x|ua(x)<a}
4.{x|ua(x)<=a}
When is a complete enumeration of solution used?
1.when a solution that
2.when there is en
3. when the modeler
4. when there are an infi
Which of the following is/are type of fuzzy interference method
1. mamdani
2.sugeno
3.rivest
4. only a and b
Who iniated idea of sofft computing
1.charles darwin
2. rich and berg
3.mc culloch
4.lofti a zadeh
A Fuzzy rule can have
1. multiple part of ante
2.only single part of
3.multiple part of ant
4. only single part of ante
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 co1.m{0/a,0.7/b,0.8/c,0.2/
2.{0/a,0.9/b,0.7/c,0
3.{0.8/a,0.7/b,0.8/c,0
4.{0/a,0.7/b,0.8/c,0.9/d,
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 inte1.{0.6/a,0.3/b,0.1/c,0.3
2. {0.6/a,0.8/b,0.1/c
3.{0.6/a,0.3/b,0.1/c,0
4.{0.6/a,0.3/b,0.2/c,0.3/
All of the follwing are suitable problem for genetic algorithm EXCEPT
1.pattern recognization
2.simulation of biol
3.simple optimization
4.dynamic process contr
All of the follwing are true about heuristics EXCEPT
1.heuristics are used w
2.heuristics are use
3.heuristics are used
4.heuristics are rules of
Applying recombination and mutation leads to a set of new candidates, called as ?
1.sub parents
2.parents
3.offsprings
4.grand child
Artificial neural network is used for
1.pattern recognition
2.classification
3.clustering
4.all of the above
can a crisp set be a fuzzy set?
1. no
2.yes
3.depends
4.All of the above
Chromosomes are actually ?
1. line representation
2.string representa
3.circular representat
4.all of these
Control actions while computing should be
1.ambiguous
2.unambioguos
3.inaccurate
4.None of These
Core of soft computing is
1.fuzzy computing,neu
2.fuzzy network an
3.neural science
4.genetic science
Determining the duration of the simulation occurs before the model is validated and te
1.true
2.false
3.Noise
4.all
EC stands for?
1.evolutionary comput
2.evolutionary com
3.electronic computa
4.noneof these
Elements of ES are/is
1.parent population siz
2.survival populatio
3. both a and b
4.None of these
EV is dominantly used for solving .
1.optimization proble
2.mnp problem
3.simple problems
4.noneof these
Evolution Strategies is developed with
1.selection
2.mutation
3.a population of size
4.all of these
Evolution Strategies typically uses
1.real-valued vector re
2.vector representa
3.time based represe
4. none of these
Evolution Strategies typically uses
1.real-valued vector re
2.vector representa
3.time based represe
4. none of these
Evolutionary algorithms are a based approach
1. heuristic
2.metaheuristic
3.both a and b
4.noneof these
Evolutionary programming was developef by
1.fredrik
2.fodgel
3.frank
4.. flin
Fuzzy logic deals with which of the following
1.fuzzy set
2.fuzzy algebra
3.both a and b
4.None of the above
Fuzzy logic is a form of
1.two valued logic
2.crisp set logic
3.many value logic
4.binary set logic
GA stands for
1.genetic algorithm
2.genetic asssuranc
3.genese alforithm
4.noneof these
GBML stands for
1. genese based machi
2.genes based mob
3.genetic bsed machi
4.noneof these
Genetic algorithm belong to the family of method in the
1. artifical intelligence a
2.optimization area
3.complete enumerat
4. non computer based i
Hard computing is also called as
1.evolutionary comput
2.conventional com
3.non conventional co
4.probablistic computing
Hard computing perfforms what type of computation
1.sequential
2.parallel
3.approxiamate
4.both a and b
How does blind search differ from optimization
1.blind search represe
2.blind search usua
3.blind search cannot
4.none of these
in ES survival is
1. indeterministic
2.deterministic
3.both a and b
4.none of these
In modeling,an optimal solution is understood to be
1.a solution that can o
2.a solution found
3. a solution that is th
4.a solution that require
In soft computing the problems,algorithms can be
1.non adaptive
2.adaptive
3.static
4.all of the above
LCS belongs to based methods?
1.rule based learning
2.genetic learning
3. both a and b
4.noneof these
mutation is applied on candidates.
1.one
2.two
3.more than two
4. noneof these
Neural network computing
1.mimics human behav
2. information proce
3.both a and b
4.none of the above
Parameters that affect GA
1. initial population
2. selection process
3.. fitness function
4.all of these
recombination is applied on candidates.
1.one
2.two
3.more than two
4.noneof these
Soft computing is based on
1.fuzzy logic
2.neural science
3.crisp software
4. binary logic
Survival is approach.
1.deteministic
2.non deterministic
3.semi deterministic
4.noneof these
The bandwidth(A) in a fuzzy set is given by
1.(a)=|x1*x2|
2. (a)=|x1+x2|
3. (a)=|x1-x2|
4.(a)=|x1/x2|
The intersection of two fuzzy sets is the of each element from two sets
1. maximum
2.minimum
3.equal to
4.not equal to
The process of fuzzy interference system involes
1.membership function
2.fuzzy logic operat
3. if-then rules
4.All of the above
The union of two fuzzy sets is the of each element from two sets
1.maximum
2.minimum
3.equal to
4.not equal to
What are different types of crossover
1.discrete and interme
2. discrete and conti
3.continuous and inte
4.none of these
what are the parameters that affect GA are/is
1.selection process
2.initial population
3.both a and b
4. none of these
What denotes the core(A) in a fuzzy set?
1. A. {x|ua(x)>0}
2.{x|ua(x)=1}
3. {x|ua(x)>=0.5}
4.{x|ua(x)>0.8}
What does a fuzzifier do
1.coverts crisp input to
2.coverts crisp oupu
3.coverts fuzzy input
4.coverts fuzzy output to
What does the 0 membership value means in the set
1. the object is fully insi
2.the object is not
3.the object is partiall
4.None of the above
What is the first step in Evolutionary algorithm
1. termination
2.selection
3.recombination
4.initialization
When we say that the boundary is crisp
1.distinguish two regio
2.cannot distinguis
3.collection of ordere
4.None of These
Which approach is most suited to structured problem with little uncertainity
1.simuation
2.human intuition
3.optimization
4.genetic algorithm
Which computing produces accurate results
1.soft computing
2.hard computing
3.both a and b
4.None of These
Which of the folloowing is not defuzzifier method
1.centroid of area
2. mean of maximu
3.largest of maximum
4.hypotenuse of triangle
which of the following is a sequence of steps taken in designning a fuzy logic machine
1.. fuzzification->rule ev
2.deffuzification->r
3.rule evaluation->fuz
4. rule evaluation->defuz