(1+λ) ES
1.λ mutants can be generated from one parent
2.one mutant is generated
3.2λ mutants can be generated
4.no mutants are generated
Both fuzzy logic and artificial neural network are soft computing techniques because
1.both gives precise an
2.ann gives accura
3. in each, no precise
4.fuzzy gives exact resul
IF x is A and y is B then z=c (c is constant), is
1.rule in zero order fis
2.rule in first order fis
3. both a and b
4.neither a nor b
In Evolutionary programming, survival selection is
1.probabilistic selection (μ+μ) selection
2. (μ, λ)- selection based on the children only (μ+λ)- selection based on both the set of parent and children
3.children replace the parent
4.All of the mentioned
In Evolutionary strategy, recombination is
1.doesnot use recombination to produce offspring. it only uses mutation
2. uses recombination such as cross over to produce offspring
3.uses various recombination operators
4.None of the mentioned
In Evolutionary strategy, survival selection is
1.probabilistic selection (μ+μ) selection
2.(μ, λ)- selection based on the children only (μ+λ)- selection based on both the set of parent and children
3.children replace the parent
4.all the mentioned
In fuzzy propositions, ---- gives an approximate idea of the number of elements of a subset fulfilling certain conditions
1.fuzzy predicate and predicate modifiers
2.fuzzy quantifiers
3. fuzzy qualifiers
4.All of the above
Multiple conjuctives antecedents is method of ----- in FLC
1. decomposition rule
2.formation of rule
3. truth tables
4.all of the above
What are normally the two best measurement units for an evolutionary algorithm? 1. Number of evaluations 2. Elapsed time 3. CPU Time 4. Number of generations
1.1 and 2
2.2 and 3
3.3 and 4
4.1 and 4
What is the feature of ANNs due to which they can deal with noisy, fuzzy, inconsistent data?
1.associative nature of networks
2.distributive nature of networks
3.both associative & distributive
4.none of the mentioned
Which of the following operator is simplest selection operator?
1.random selection
2.proportional selection
3. tournament selection
4.none
(1+1) ES
1.operates on population size of two
2. operates on populantion size of one
3. operates on populantion size of zero
4.operates on populantion size of λ
-- defines logic funtion of two prepositions
1.prepositions
2.lingustic hedges
3. truth tables
4. inference rules
. In Evolutionary programming, recombination is
1.doesnot use recombination to produce offspring. it only uses mutation
2. uses recombination such as cross over to produce offspring
3.uses various recombination operators
4.none of the mentioned
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
1.convex fuzzy set
2.concave fuzzy set
3. non concave fuzzy set
4. non convex fuzzy set
A fuzzy set wherein no membership function has its value equal to 1 is called
1.normal fuzzy set
2.subnormal fuzzy set.
3.convex fuzzy set
4.concave fuzzy set
A fuzzy set whose membership function has at least one element x in the universe whose membership valueis unity is called
1.sub normal fuzzy sets
2.normal fuzzy set
3. convex fuzzy set
4.concave fuzzy set
A U (B U C) =
1.(a ∩ b) ∩ (a ∩ c)
2.(a ∪ b ) ∪ c
3.(a ∪ b) ∩ (a ∪ c)
4.b ∩ a ∪ c
An equivalence between Fuzzy vs Probability to that of Prediction vs Forecasting is
1. fuzzy ≈ prediction
2.fuzzy ≈ forecastin
3.probability ≈ foreca
4.none of these
Any soft-computing methodology is characterised by
1.precise solution
2. control actions are unambiguous and accurate
3.control actions is formally defined
4.algorithm which can easily adapt with the change of dynamic environment
Basic elements of EA are ?
1.parent selection methods
2.survival selection methods
3.both a and b
4.noneof these
Both fuzzy logic and artificial neural network are soft computing techniques because
1.both gives precise an
2.ann gives accura
3. in each, no precise
4.fuzzy gives exact resul
Choose the correct statement 1. A fuzzy set is a crisp set but the reverse is not true 2. If A,B and C are three fuzzy sets defined over the same universe of discourse such that A ≤ B and B ≤ C and A ≤ C 3. Membership function defines the fuzziness in a fuzzy set irrespecive of the elements in the set, which are discrete or continuous
1.1 only
2. 2 and 3
3. 1,2 and 3
4. none of these
Compute 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 as
μA+B(z) = maxx+y=z (min(μA(x), μB(x))) Then, f(A+B) is equal to1.{(0.5,12), (0.6,13), (1,
2. {(0.5,12), (0.6,13),
3. {(0.3,12), (0.5,13)
4. {(0.3,12), (0.5,13), (0.6
Consider a fuzzy set A defined on the interval X = [0, 10] of integers by the membership JunctionμA(x) = x / (x+2) Then the α cut corresponding to α = 0.5 will be
1. {0, 1, 2, 3, 4, 5, 6, 7, 8
2.{1, 2, 3, 4, 5, 6, 7,
3.{2, 3, 4, 5, 6, 7, 8, 9,
4.None of the above
EP applies which evolutionary operators?
1.variation through application of mutation operators
2.selection
3.both a and b
4.none of the mentioned
Evolutionary Strategies (ES)
1.(µ,λ): select survivors among parents and offspring
2. (µ+λ): select survivors among parents and offspring
3.(µ-λ): select survivors among offspring only
4. (µ:λ): select survivors among offspring only
Feature of ANN in which ANN creates its own organization or representation of information it receives during learning time is
1.adaptive learning
2.self organization
3.what-if analysis
4.supervised learning
For what purpose Feedback neural networks are primarily used?
1.classification
2.feature mapping
3.pattern mapping
4.none of the mentioned
Given U = {1,2,3,4,5,6,7} A = {(3, 0.7), (5, 1), (6, 0.8)}then A will be: (where ~ → complement)1.{(4, 0.7), (2,1), (1,0.8)
2.{(4, 0.3.): (5, 0), (6
3. {(l, 1), (2, 1), (3, 0.3)
4. {(3, 0.3), (6.0.2)}
If A and B are two fuzzy sets with membership functions
μA(x) = {0.6, 0.5, 0.1, 0.7, 0.8}
μB(x) = {0.9, 0.2, 0.6, 0.8, 0.5}
Then the value of μ(A∪B)’(x) will be1.{0.9, 0.5, 0.6, 0.8, 0.8
2.{0.6, 0.2, 0.1, 0.7,
3.{0.1, 0.5, 0.4, 0.2, 0
4. {0.1, 0.5, 0.4, 0.2, 0.3}
In Evolutionary programming,
1. individuals are represented by real- valued vector
2. individual solution is represented as a finite state machine
3.individuals are represented as binary string
4.none of the mentioned
Mamdani's Fuzzy Inference Method Was Designed To Attempt What?
1. control any two combinations of any two products by synthesising a set of linguistic control rules obtained from experienced human operations.
2.control any two combinations of any two products by synthesising a set of linguistic control rules obtained from experienced human operations.
3.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 synt
4.control a air craft and fuel level combination by synthesising a set of linguistic control rules obtained from experienced human operations.
Multiple disjuctives antecedents is method of ----- in FLC
1.decomposition rule
2.formation of rule
3. truth tables
4.all of the above
Operations in the neural networks can perform what kind of operations?
1.serial
2.parallel
3.serial or parallel
4.none of the mentioned
Step size in dynamic EP :
1.deviation in step sizes remain static
2.deviation in step sizes change over time using some deterministic function
3.deviation in step size change dynamically
4.size=1
Step size in non-adaptive EP :
1.deviation in step sizes remain static
2.deviation in step sizes change over time using some deterministic function
3.deviation in step size change dynamically
4.size=1
Step size in self-adaptive EP :
1. deviation in step sizes remain static
2.deviation in step sizes change over time using some deterministic function
3.deviation in step size change dynamically
4.size=1
Termination condition for EA
1.mazimally allowed cpu time is elapsed
2.total number of fitness evaluations reaches a given limit
3.population diveristy drops under a given threshold
4. all the mentioned
The fuzzy proposition "IF X is E then Y is F" is a
1.conditional unqualifi
2.unconditional unq
3.conditional qualifie
4.unconditional qualified
The values of the set membership is represented by
1.discrete set
2.degree of truth
3.probabilities
4.both degree of truth& probabilities
There are also other operators, more linguistic in nature, called
that can be applied to fuzzy set theory.1.hedges
2.lingual variable
3.fuzz variable
4.none of the mentioned
What Are The Two Types Of Fuzzy Inference Systems?
1.model-type and system-type
2.momfred-type and semigi-type
3.mamdani-type and sugeno-type
4.mihni-type and sujgani-type
What Is Another Name For Fuzzy Inference Systems?
1.. fuzzy expert system
2.fuzzy modelling
3.fuzzy logic controller
4.All of the above
What is ART in neural networks?
1.automatic resonance theory
2.artificial resonance theory
3.adaptive resonance theory
4.none of the mentioned
Which crossover operators are used in evolutionary programming?
1.single point crossover
2.two point crossover
3.uniform crossover
4.evolutionary programming doesnot use crossover operators
Which of the following neural networks uses supervised learning? (A) Multilayer perceptron (B) Self organizing feature map (C) Hopfield network
1. (a) only
2.(b) only
3.(a) and (b) only
4. (a) and (c) only
Which of these emphasize of development of behavioral models?
1.evolutionary programming
2.genetic programming
3.genetic algorithm
4.all the mentioned
Which selection strategy works with negative fitness value?
1.roulette wheel selection
2.stochastic universal sampling
3. tournament selection
4.rank selection