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

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Question:
 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

Posted Date:-2022-07-13 06:18:10

More MCQS Questions and answers

  1. (1+λ) ES
  2. Both fuzzy logic and artificial neural network are soft computing techniques because
  3. IF x is A and y is B then z=c (c is constant), is
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  6. In Evolutionary strategy, survival selection is
  7. In fuzzy propositions, ---- gives an approximate idea of the number of elements of a subset fulfilling certain conditions
  8. Multiple conjuctives antecedents is method of ----- in FLC
  9. 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
  10. What is the feature of ANNs due to which they can deal with noisy, fuzzy, inconsistent data?
  11. Which of the following operator is simplest selection operator?
  12. -- defines logic funtion of two prepositions
  13. . In Evolutionary programming, recombination is
  14. (1+1) ES
  15. 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
  16. A fuzzy set wherein no membership function has its value equal to 1 is called
  17. A fuzzy set whose membership function has at least one element x in the universe whose membership valueis unity is called
  18. A U (B U C) =
  19. An equivalence between Fuzzy vs Probability to that of Prediction vs Forecasting is
  20. Any soft-computing methodology is characterised by
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  30. Given U = {1,2,3,4,5,6,7} A = {(3, 0.7), (5, 1), (6, 0.8)}then A will be: (where ~ → complement)
  31. 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 be
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  49. Which selection strategy works with negative fitness value?
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