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120+ Computer Engineering Soft Computing Solved MCQs

These multiple-choice questions (MCQs) are designed to enhance your knowledge and understanding in the following areas: Computer Science Engineering (CSE) .

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101.

In Evolutionary programming, survival selection is

A. probabilistic selection (μ+μ) selection
B. (μ, λ)- selection based on the children only (μ+λ)- selection based on both the set of parent and children
C. children replace the parent
D. all the mentioned
Answer» A. probabilistic selection (μ+μ) selection
discuss
102.

In Evolutionary strategy, survival selection is

A. probabilistic selection (μ+μ) selection
B. (μ, λ)- selection based on the children only (μ+λ)- selection based on both the set of parent and children
C. children replace the parent
D. all the mentioned
Answer» B. (μ, λ)- selection based on the children only (μ+λ)- selection based on both the set of parent and children
discuss
103.

In Evolutionary programming, recombination is

A. doesnot use recombination to produce offspring. it only uses mutation
B. uses recombination such as cross over to produce offspring
C. uses various recombination operators
D. none of the mentioned
Answer» A. doesnot use recombination to produce offspring. it only uses mutation
discuss
104.

In Evolutionary strategy, recombination is

A. doesnot use recombination to produce offspring. it only uses mutation
B. uses recombination such as cross over to produce offspring
C. uses various recombination operators
D. none of the mentioned
Answer» B. uses recombination such as cross over to produce offspring
discuss
105.

Step size in non-adaptive EP :

A. deviation in step sizes remain static
B. deviation in step sizes change over time using some deterministic function
C. deviation in step size change dynamically
D. size=1
Answer» A. deviation in step sizes remain static
discuss
106.

Step size in dynamic EP :

A. deviation in step sizes remain static
B. deviation in step sizes change over time using some deterministic function
C. deviation in step size change dynamically
D. size=1
Answer» B. deviation in step sizes change over time using some deterministic function
discuss
107.

Step size in self-adaptive EP :

A. deviation in step sizes remain static
B. deviation in step sizes change over time using some deterministic function
C. deviation in step size change dynamically
D. size=1
Answer» C. deviation in step size change dynamically
discuss
108.

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

A. 1 and 2
B. 2 and 3
C. 3 and 4
D. 1 and 4
Answer» D. 1 and 4
discuss
109.

Evolutionary Strategies (ES)

A. (µ,λ): select survivors among parents and offspring
B. (µ+λ): select survivors among parents and offspring
C. (µ-λ): select survivors among offspring only
D. (µ:λ): select survivors among offspring only
Answer» B. (µ+λ): select survivors among parents and offspring
discuss
110.

In Evolutionary programming,

A. individuals are represented by real- valued vector
B. individual solution is represented as a finite state machine
C. individuals are represented as binary string
D. none of the mentioned
Answer» B. individual solution is represented as a finite state machine
discuss
111.

In Evolutionary Strategy,

A. individuals are represented by real- valued vector
B. individual solution is represented as a finite state machine
C. individuals are represented as binary string
D. none of the mentioned
Answer» A. individuals are represented by real- valued vector
discuss
112.

(1+1) ES

A. offspring becomes parent if offspring\s fitness is as good as parent of next generation
B. offspring become parent by default
C. offspring never becomes parent
D. none of the mentioned
Answer» A. offspring becomes parent if offspring\s fitness is as good as parent of next generation
discuss
113.

(1+λ) ES

A. λ mutants can be generated from one parent
B. one mutant is generated
C. 2λ mutants can be generated
D. no mutants are generated
Answer» A. λ mutants can be generated from one parent
discuss
114.

Termination condition for EA

A. mazimally allowed cpu time is elapsed
B. total number of fitness evaluations reaches a given limit
C. population diveristy drops under a given threshold
D. all the mentioned
Answer» D. all the mentioned
discuss
115.

Which of the following operator is simplest selection operator?

A. random selection
B. proportional selection
C. tournament selection
D. none
Answer» A. random selection
discuss
116.

Which crossover operators are used in evolutionary programming?

A. single point crossover
B. two point crossover
C. uniform crossover
D. evolutionary programming doesnot use crossover operators
Answer» D. evolutionary programming doesnot use crossover operators
discuss
117.

(1+1) ES

A. operates on population size of two
B. operates on populantion size of one
C. operates on populantion size of zero
D. operates on populantion size of λ
Answer» A. operates on population size of two
discuss
118.

Which of these emphasize of development of behavioral models?

A. evolutionary programming
B. genetic programming
C. genetic algorithm
D. all the mentioned
Answer» A. evolutionary programming
discuss
119.

EP applies which evolutionary operators?

A. variation through application of mutation operators
B. selection
C. both a and b
D. none of the mentioned
Answer» C. both a and b
discuss
120.

Which selection strategy works with negative fitness value?

A. roulette wheel selection
B. stochastic universal sampling
C. tournament selection
D. rank selection
Answer» D. rank selection
discuss

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