# Soft Computing and Optimisation Algorithms MCQs for Computer Engineering

#### 1. When we say that the boundary is crisp

A: Distinguish two regions clearly
B: Cannot Distinguish two regions clearly
C: Collection of ordered pairs
D: None of these

Answer: A: Distinguish two regions clearly

#### 2. Fuzzy logic is a form of

A: two valued logic
B: crisp set logic
C: many value logic
D: binary set logic

A: Consequent
B: Outfeed
C: Anticedents
D: Premise

A: Ambiguous
B: Unambiguous
C: Inaccurate
D: None of these

#### 5. Core of soft computing is

A: Fuzzy computing, neural computing, Genetic algorithm
B: Fuzzy network and artificial intelligence
C: Neural Science
D: Genetic Science

Answer: A: Fuzzy computing, neural computing, Genetic algorithm

A: Sequential
B: Parallel
C: approximate
D: both a and b

#### 7. Who iniated idea of soft computing

A: Charles Darwin
B: Rich and Berg
C: McCulloch

#### 8. Soft computing is based on

A: fuzzy logic
B: neural science
C: crisp software
D: binary logic

#### 9. In soft computing the problems,algorithms can be

C: static
D: all of the above

#### 10. Fuzzy Computing

A: mimics human behavior
B: deals with imprecise, probabilistic
C: exact information
D: both a and b

Answer: D: both a and b

#### 11. Hard computing is also called as

A: evolutionary computing
B: conventional computing
C: non-conventional computing
D: probabilistic computing

#### 12. Which computing produces accurate results

A: soft computing
B: hard computing
C: both a and b
D: none of the above

#### 13. Neural network computing

A: mimics human behavior
C: both a and b
D: none of the above

Answer: C: both a and b

#### 14. Artificial neural network is used for

A: pattern recognition
B: classification
C: clustering
D: all of the above

Answer: D: all of the above

#### 15. How does blind search differ from optimization

A: Blind search represent a guided approach while optimization is unguided
B: Blind search usually does not conclude in one step like some optimization methods.
C: Blind search cannot result in optimal solution whereas optimization methods does
D: none of these

Answer: B: Blind search usually does not conclude in one step like some optimization methods.

#### 16. In modeling, an optimal solution is understood to be

A: a solution that can only be determined by an exhaustive enumeration testing of alternatives
B: a solution found in the least possible time and using the least possible computing resources
C: a solution that is the best based on criteria defined in the design phase
D: a solution that requires an algorithm for the determination

Answer: C: a solution that is the best based on criteria defined in the design phase

#### 17. When is a complete enumeration of solution used?

A: When a solution that is “good enough” is fine and good heuristics are available
B: When there is enough time and computational power available
C: When the modeler requires a guided approach to problem-solving
D: When there is an infinite number of solutions to be searched

Answer:B: When there is enough time and computational power available

#### 18. All of the following are true about heuristics EXCEPT

A: heuristics are used when the modeler requires a guided approach to problem-solving
B: heuristics are used when a solution that is “good enough” is sought
C: heuristics are used when there is abundant time and computational power
D: heuristics are rules of good judgment

Answer:C: heuristics are used when there is abundant time and computational power

#### 19. Which approach is most suited to structured problem with little uncertainity

A: Simuation
B: human intuition
C: Optimization
D: genetic algorithm

#### 20. Genetic algorithm belong to the family of method in the

A: artificial intelligence area
B: optimization area
C: complete enumeration family of methods
D: Non-computer based isolation area

#### 21. What does the 0 membership value means in the set

A: the object is fully inside the set
B: the object is not in the set
C: the object is partially present in the set
D: none of the above

Answer:B: the object is not in the set

A: maximum
B: minimum
C: equal to
D: not equal to

#### 23. The process of fuzzy interference system involes

A: membership functions
B: fuzzy logic operators
C: if-then rules
D: all the above

#### 24. What does a fuzzifier do

A: coverts crisp input to linguistic variables
B: coverts crisp output to linguistic variables
C: coverts fuzzy input to linguistic variables
D: coverts fuzzy output to linguistic variables

Answer:A: coverts crisp input to linguistic variables

#### 25. Which of the following is not defuzzifier method

A: centroid of an area
B: mean of maximum
C: largest of maximum
D: hypotenuse of the triangle

A: Mamdani
B: Sugeno
C: rivest
D: only a and b

#### 27. A Fuzzy rule can have

A: multiple parts of the antecedent, an only single part of the consequent
B: only single part of the antecedent, multiple part of the consequent
C: multiple parts of the antecedent, multiple parts of the consequent
D: only single part of the antecedent, an only single part of the consequent

Answer:C: multiple part of antecedent, multiple part of consequent

A: {x|Ua(x)>a}
B: {x|Ua(x)>=a}
C: {x|Ua(x)

A: (A)=|x1*x2|
B: (A)=|x1+x2|
C: (A)=|x1-x2|
D: (A)=|x1/x2|

A: maximum
B: minimum
C: equal to
D: not equal to

#### 31. 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 complement of A?

A: {0/a,0.7/b,0.8/c,0.2/d,1/e}
B: {0/a,0.9/b,0.7/c,0.2/d,1/e}
C: {0.8/a,0.7/b,0.8/c,0.7/d,1/e}
D: {0/a,0.7/b,0.8/c,0.9/d,1/e}

#### 32. 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}

#### 33. 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 intersection of A and B ?

A: {0.6/a,0.3/b,0.1/c,0.3/d,0/e}
B: {0.6/a,0.8/b,0.1/c,0.3/d,0/e}
C: {0.6/a,0.3/b,0.1/c,0.5/d,0/e}
D: {0.6/a,0.3/b,0.2/c,0.3/d,1/e}

A: {x|Ua(x)>0}
B: {x|Ua(x)<0}
C: {x|Ua(x)<=0}
D: {x|Ua(x)<0.5}

#### 35. Fuzzy logic deals with which of the following

A: fuzzy set
B: fuzzy algebra
C: both a and b
D: none of the above

#### 36. Which of the following is a sequence of steps taken in designing a fuzzy logic machine

A: Fuzzification->Rule Evaluation->Deffuzification
B: Deffuzification->Rule evaluation->Fuzzification
C: Rule evaluation>Fuzzification>Deffuzification
D: Rule evaluation->Defuzzification->Fuzzification

#### 37. can a crisp set be a fuzzy set?

A: no
B: yes
C: depends
D: all of the above

#### 38. Genetic algorithm belong to the family of method in the

A: artificial intelligence area
B: optimization area
C: complete enumeration family of methods
D: Non-computer based isolation area

#### 39. All of the following are a suitable problems for genetic algorithms EXCEPT

A: pattern recognization
B: simulation of biological models
C: simple optimization with few variables
D: dynamic process control

Answer:C: simple optimization with few variables

#### 40. Genetic algorithms are example of

A: heuristic
B: Evolutionary algorithm
C: ACO
D: PSO

A: one
B: two
C: more than two
D: none of these

A: one
B: two
C: more than two
D: none of these

#### 43. LCS belongs to ___ based methods?

A: rule-based learning
B: genetic learning
C: both a and b
D: none of these

#### 44. Survival is ___ approach.

A: deterministic
B: non deterministic
C: semi deterministic
D: none of these

A: heuristic
B: metaheuristic
C: both a and b
D: none of these

#### 46. Tabu search is an example of ?

A: heuristic
B: Evolutionary algorithm
C: ACO
D: PSO

A: machines
B: Birds
C: ACO
D: genetics

#### 48. Chromosomes are actually?

A: line representation
B: String representation
C: Circular representation
D: all of these

#### 49. What are the parameters that affect GA are/is

A: selection process
B: initial population
C: both a and b
D: none of these

A: Fredrik
B: Fodgel
C: Frank
D: Flin

#### 51. EC stands for?

A: Evolutionary Computations
B: Evolutionary computer
C: Electronic computations
D: none of these

#### 52. _____does not 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

#### 53. 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:A: middle or low level of abstractions

#### 54. _________cannot easily be transferred from one problem domain to another

A: optimal solution
B: analytical solution
C: simulation solution
D: none of these

#### 55. What are different types of crossover

A: discrete and intermedium
B: discrete and continuous
C: continuous and intermedium
D: none of these

#### 56. Elements of ES are/is

A: Parent population size
B: Survival population size
C: both a and b
D: none of these

#### 57. What is the first step in Evolutionary algorithm

A: Termination
B: selection
C: Recombination
D: Initialization

#### 58. in ES survival is

A: indeterministic
B: deterministic
C: both a and b
D: none of these

#### 59. Evolution Strategies typically uses

A: real-valued vector representations
B: vector representation
C: time-based representation
D: none of these