Computer Engineering Soft Computing MCQs with answers Page - 7

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Q. 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

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Q. (1+1) ES

  • (A) offspring becomes parent if offsprings 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

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Q. (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

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Q. 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

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Q. Which of the following operator is simplest selection operator?

  • (A) random selection
  • (B) proportional selection
  • (C) tournament selection
  • (D) none

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Q. 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

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Q. (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

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Q. Which of these emphasize of development of behavioral models?

  • (A) evolutionary programming
  • (B) genetic programming
  • (C) genetic algorithm
  • (D) all the mentioned

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Q. EP applies which evolutionary operators?

  • (A) variation through application of mutation operators
  • (B) selection
  • (C) both a and b
  • (D) none of the mentioned

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Q. Which selection strategy works with negative fitness value?

  • (A) roulette wheel selection
  • (B) stochastic universal sampling
  • (C) tournament selection
  • (D) rank selection

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