MCQOPTIONS
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MCQOPTIONS
This section includes 213 Mcqs, each offering curated multiple-choice questions to sharpen your Uncategorized topics knowledge and support exam preparation. Choose a topic below to get started.
| 1. |
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 union of AUB? |
| A. | {1/a,0.9/b,0.1/c,0.5/d,0.2/e} |
| B. | {0.8/a,0.9/b,0.2/c,0.5/d,0.2/e} |
| C. | {1/a,0.9/b,0.2/c,0.8/d,0.2/e} |
| D. | {1/a,0.9/b,0.2/c,0.8/d,0.8/e} |
| Answer» D. {1/a,0.9/b,0.2/c,0.8/d,0.8/e} | |
| 2. |
Determining the duration of the simulation occurs before the model is validated and tested. |
| A. | true |
| B. | false |
| Answer» C. | |
| 3. |
_____doesnot usually allow decision makers to see how a solution to a ___________envolves over time nor can decision makers interact with it. |
| A. | simulation ,complex problem |
| B. | simulation,easy problem |
| C. | genetics,complex problem |
| D. | genetics,easy problem |
| Answer» B. simulation,easy problem | |
| 4. |
_________cannot easily be transferred from one problem domain to another |
| A. | optimal solution |
| B. | analytical solution |
| C. | simulation solutuon |
| D. | none of these |
| Answer» D. none of these | |
| 5. |
Discrete events and agent-based models are usuallly used for_____________. |
| A. | middle or low level of abstractions |
| B. | high level of abstraction |
| C. | very high level of abstraction |
| D. | none of these |
| Answer» B. high level of abstraction | |
| 6. |
EV is dominantly used for solving ___. |
| A. | optimization problems |
| B. | np problem |
| C. | simple problems |
| D. | noneof these |
| Answer» B. np problem | |
| 7. |
____ decides who becomes parents and how many children the parents have. |
| A. | parent combination |
| B. | parent selection |
| C. | parent mutation |
| D. | parent replace |
| Answer» C. parent mutation | |
| 8. |
Which of the following neural networks uses supervised learning?(A) Multilayer perceptron(B) Self organizing feature map(C) Hopfield network |
| A. | (a) only |
| B. | (b) only |
| C. | (a) and (b) only |
| D. | (a) and (c) only |
| Answer» B. (b) only | |
| 9. |
Features of GA |
| A. | a string representation of chromosomes. |
| B. | a fitness function be to minimized. |
| C. | a cross-over method and a mutation method. |
| D. | all of these |
| Answer» E. | |
| 10. |
GP individual stores computer program |
| A. | true |
| B. | false |
| Answer» B. false | |
| 11. |
EV is used for |
| A. | solving optimization problems |
| B. | finding solutions |
| C. | both a and b |
| D. | none of these |
| Answer» B. finding solutions | |
| 12. |
Ability to learn how to do task based on the data is done by |
| A. | self organization |
| B. | adaptive learning |
| C. | fault tolerance |
| D. | robustness |
| Answer» C. fault tolerance | |
| 13. |
Who can deal with noisy input information |
| A. | soft computing |
| B. | hard computing |
| C. | both a and b |
| D. | none of the above |
| Answer» B. hard computing | |
| 14. |
Which of the following is not a technique of soft computing |
| A. | neural network |
| B. | genetic algorithm |
| C. | evolutionary algorithm |
| D. | conventional algorithm |
| Answer» E. | |
| 15. |
Fuzzy logic system is based on what type of rule |
| A. | if-then |
| B. | else-if |
| C. | while |
| D. | do-while |
| Answer» B. else-if | |
| 16. |
Which approach is most suited to complex problem with significant uncertainty, a need for experimentation, and time compression? |
| A. | simulation |
| B. | optimization |
| C. | human intution |
| D. | genetic algorithm |
| Answer» B. optimization | |
| 17. |
What BEST describes a simulation model in which it is not important to know exactly when a modeled event occurred |
| A. | continuous distribution simulation |
| B. | time dependent simulation |
| C. | system dynamics simulation |
| D. | discrete event simulation |
| Answer» C. system dynamics simulation | |
| 18. |
Which of the following is the advantage of simulation? |
| A. | it can incorporate significant real-life complexity |
| B. | it always result in optimal solution |
| C. | simulation software requires special skils |
| D. | it solves problem in one pass with no iteration. |
| Answer» B. it always result in optimal solution | |
| 19. |
The defining length of a schema is useful to calculate ______of the schema for__________. |
| A. | survival probability,crossovers |
| B. | crossovers,survival probability |
| C. | crossovers,length |
| D. | length,crossover |
| Answer» B. crossovers,survival probability | |
| 20. |
Evaporation of pharomones is ? |
| A. | directly proportional to path length |
| B. | inversly proportional to path length |
| C. | constant |
| D. | none |
| Answer» B. inversly proportional to path length | |
| 21. |
R=(AXB)U( XY) is |
| A. | Zadeh's Max Product rule for If x is A then y is B else y is C |
| B. | Zadeh's Max Min rule for If x is A then y is B |
| C. | Zadeh's Max Product rule for If x is A then y is B else y is C |
| D. | Zadeh's Max Min rule for If x is A then y is B |
| Answer» E. | |
| 22. |
A fuzzy set A is closed if: |
| A. | lim x (x) = 1 and lim x + (x) = |
| B. | lim x (x) = lim x + (x) = 0 |
| C. | lim x (x) = 0 and lim x + (x) = 1 |
| D. | lim x (x) = lim x + (x) = 1 |
| Answer» C. lim x (x) = 0 and lim x + (x) = 1 | |
| 23. |
Breeding in GA flow is- |
| A. | Create a mating pool- Select a pair- Reproduce |
| B. | Select a pair-Create a mating pool- Reproduce |
| C. | Reproduce-Create a mating pool- Select a pair |
| D. | None |
| Answer» B. Select a pair-Create a mating pool- Reproduce | |
| 24. |
Real Coded GA flow is- |
| A. | Random mutation- Polynomial mutation |
| B. | Polynomial mutation-Random mutation |
| C. | Flipping-Random mutation- Polynomial mutation |
| D. | None |
| Answer» B. Polynomial mutation-Random mutation | |
| 25. |
Binary Coded GA flow is- |
| A. | Flipping- Interchanging- Reversing |
| B. | Reversing- Flipping- Interchanging- |
| C. | Interchanging- Reversing-Flipping |
| D. | None |
| Answer» B. Reversing- Flipping- Interchanging- | |
| 26. |
Dispositional reasoning form of fuzzy reasoning |
| A. | the antecedent part of the rule does not contain any fuzzy quantifiers and fuzzy probabilities |
| B. | the antecedents and consequents have fuzzy linguistic variables |
| C. | antecedents with fuzzy quantifiers are related to inference rules |
| D. | antecedents are dispositions |
| Answer» E. | |
| 27. |
categories of EA are/is |
| A. | genetic algorithm |
| B. | genetic programing |
| C. | learning classifier systems |
| D. | all of these |
| Answer» E. | |
| 28. |
Phases in which the LCS individuals are evaluated are |
| A. | performance phase |
| B. | reinforcement phase |
| C. | both a and b |
| D. | none of these |
| Answer» D. none of these | |
| 29. |
MA sometimes called as |
| A. | hybrid ea |
| B. | integrated ea |
| C. | both a and b |
| D. | none of these |
| Answer» B. integrated ea | |
| 30. |
payoffs can be easily translated to a ___ function for an EA. |
| A. | survival |
| B. | reduction |
| C. | comination |
| D. | fitness |
| Answer» E. | |
| 31. |
What is defuzzification |
| A. | conversion of fuzzy set to crisp set |
| B. | conversion of crisp set to fuzzy set |
| C. | conversion of fuzzy set to fuzzy logic |
| D. | conversion of crisp set to crisp logic |
| Answer» B. conversion of crisp set to fuzzy set | |
| 32. |
To encode chromosomes which encoding schemes are used |
| A. | binary encoding |
| B. | finite state machine encoding |
| C. | real value encoding |
| D. | all of the above |
| Answer» E. | |
| 33. |
How many genes will be in the alphabet of the algorithm? |
| A. | n*(n-1)/2 |
| B. | n*(n+1)/2 |
| C. | n*(n-2)/2 |
| D. | n*(n+2)/2 |
| Answer» B. n*(n+1)/2 | |
| 34. |
ConsiderA = {1.0, 0.20, 0.75}B = {0.2, 0.45, 0.50}A B is |
| A. | {1.0, 0.45, 0.75} |
| B. | {0.2, 0.20, 0.50} |
| C. | {0.2, 0.45, 0.50} |
| D. | {1, 0.45, 1} |
| Answer» C. {0.2, 0.45, 0.50} | |
| 35. |
ConsiderA = {1.0, 0.20, 0.75}B = {0.2, 0.45, 0.50}A U B is |
| A. | {1.0, 0.45, 0.75} |
| B. | {1,0.2,0.75} |
| C. | {0.2, 0.45, 0.50} |
| D. | {1, 0.45, 1} |
| Answer» B. {1,0.2,0.75} | |
| 36. |
Syllogistic reasoning form of fuzzy reasoning |
| A. | the antecedent part of the rule does not contain any fuzzy quantifiers and fuzzy probabilities |
| B. | the antecedents and consequents have fuzzy linguistic variables |
| C. | antecedents with fuzzy quantifiers are related to inference rules |
| D. | antecedents are dispositions |
| Answer» D. antecedents are dispositions | |
| 37. |
Categorial reasoning form of fuzzy reasoning |
| A. | the antecedent part of the rule does not contain any fuzzy quantifiers and fuzzy probabilities |
| B. | the antecedents and consequents have fuzzy linguistic variables |
| C. | antecedents with fuzzy quantifiers are related to inference rules |
| D. | antecedents are dispositions |
| Answer» B. the antecedents and consequents have fuzzy linguistic variables | |
| 38. |
Genetic algorithm is a subset of_______. |
| A. | evolutionary algorithm |
| B. | dynamcic algorithm |
| C. | both a&b |
| D. | none of these |
| Answer» B. dynamcic algorithm | |
| 39. |
Qualitative reasoning form of fuzzy reasoning |
| A. | the antecedent part of the rule does not contain any fuzzy quantifiers and fuzzy probabilities |
| B. | the antecedents and consequents have fuzzy linguistic variables |
| C. | antecedents with fuzzy quantifiers are related to inference rules |
| D. | antecedents are dispositions |
| Answer» C. antecedents with fuzzy quantifiers are related to inference rules | |
| 40. |
What Is The Purpose Of Aggregation? |
| A. | to gather all the different fuzzy set outputs and combine them into a single fuzzy set outputs |
| B. | to gather all the possible inputs and use the average to gain an output |
| C. | to gather all the different fuzzy set outputs and average them out to get a single value |
| D. | to subtract all the output fuzzy set values from the input values |
| Answer» B. to gather all the possible inputs and use the average to gain an output | |
| 41. |
NP hard problems are also called as________. |
| A. | dicrete optimization |
| B. | combinatorial optimization |
| C. | evolutionary optimization |
| D. | none of these |
| Answer» C. evolutionary optimization | |
| 42. |
Genetic algorithm is first introduce by_______. |
| A. | charles darwin |
| B. | john holland |
| C. | gregor johan mendel |
| D. | none of these |
| Answer» C. gregor johan mendel | |
| 43. |
_________ decomposes two distinct solutions and then randomly mixes their parts to form novel solutions. |
| A. | selection |
| B. | recombination |
| C. | mutation |
| D. | none of these |
| Answer» C. mutation | |
| 44. |
__________ replicates the most successful solutions found in a population at a rate proportional to relative quality. |
| A. | selection |
| B. | recombination |
| C. | mutation |
| D. | none of these |
| Answer» B. recombination | |
| 45. |
__________ randomly perturbs a candidate solution. |
| A. | selection |
| B. | recombination |
| C. | mutation |
| D. | none of these |
| Answer» D. none of these | |
| 46. |
Which of the following computing technique has the ability of learing and adoption |
| A. | neural network |
| B. | evolutionary |
| C. | hard |
| D. | probabilistic |
| Answer» B. evolutionary | |
| 47. |
{0,1,#} is the symbol alphabet ,where # is a special ______symbol. |
| A. | wild card |
| B. | schema |
| C. | layout |
| D. | none of these |
| Answer» B. schema | |
| 48. |
A ________ is a template consisting of a string composed of three symbol. |
| A. | wild symbol |
| B. | schema |
| C. | layout |
| D. | none of these |
| Answer» C. layout | |
| 49. |
The ants prefer the smaller drop of honey over the more abundant, but less nutritious, sugar. This is the example of? |
| A. | kruskal algorithm |
| B. | travelling salesman |
| C. | knapsack problem |
| D. | np hard problem |
| Answer» D. np hard problem | |
| 50. |
In search techniques, as single point based contradicts population based similary deterministic contradicts ___? |
| A. | stochastic |
| B. | simplex based |
| C. | complex based |
| D. | none |
| Answer» B. simplex based | |