Soft Computing MCQ

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Question 1 : Which of the following can be used for clustering of data ?

  1. Single layer perception
  2. Multilayer perception
  3. Self organizing map
  4. Gradient Descent Method.
    

Question 2 : Which Statements is true regarding Biological neuron?

  1. A Biological neuron has only one input and only one output.
  2. A Biological neuron can have only one input but multiple output.
  3. A Biological neuron can have multiple input and multiple output.
  4. A Biological neuron can have multiple input but only single output.
    

Question 3 : Which of the following is not true about Perceptrons ?

  1. It can classify linearly separable patterns
  2. It has only one output unit
  3. It does not have any hidden layer
  4. It can not classify linearly separable patterns
    

Question 4 : For Neuron, if w1=2, w2= -1 and input vector X=[0.8 1.2] and desired output d= 1, Determine value of T .

  1. T= 1
  2. T= 0
  3. T= 0.4
  4. T= -0.3
    

Question 5 : What are the 2 types of learning?

  1. Improvised and un-improvised
  2. Supervised and unsupervised
  3. Layered and un-layered
  4. Deterministic and non deterministic
    

Question 6 : For Perceptron learning, the bias and the threshold are:

  1. Interchangable
  2. Non Interchangable
  3. Conditionally Interchangable
  4. always equal
    

Question 7 : The square root of fuzzy set is called _____.

  1. Dilemma
  2. Dual
  3. Concentration
  4. Root mean square
    

Question 8 : What is a way of representing individual genes?

  1. Conversion
  2. Encoding
  3. Coding
  4. Decoding
    

Question 9 : The method of steepest descent, is popularly known as :

  1. Gradient method
  2. Downhill method
  3. Complex method
  4. Stochastic method
    

Question 10 : What was the name of the first model which simulated the working of human brain?

  1. McCulloch-pitts neuron model
  2. Marvin Minsky neuron model
  3. Hopfield model of neuron
  4. Rosenblatt
    

Question 11 : How many layers are there in adaptive neuro-fuzzy inference systems (ANFIS) ?

  1. 3
  2. 5
  3. 7
  4. 4
    

Question 12 : An input to a fuzzy inference system is a :

  1. A crisp value
  2. A constant value
  3. A fuzzy set
  4. a linguistic variable
    

Question 13 : In the neuron, attached to the soma are long irregularly shaped filaments called:

  1. Dendrites
  2. Axon
  3. Synapse
  4. Cerebellum
    

Question 14 : Choose the correct optimization technique.

  1. Evolutionary computing
  2. Mathematical Modelling
  3. Cylindrical geometry
  4. Adaptive calculus
    

Question 15 : Which of the following transformations on membership functions of fuzzy sets enhances the membership values ?

  1. Dilation
  2. Concentration
  3. Intensification
  4. Fuzzification
    

Question 16 : What do you mean by the statement :The genes from the already discovered good individuals are exploited.

  1. Convergence
  2. Population diversity
  3. Scarcity
  4. Population fitness
    

Question 17 : From the below mentioned systems, choose the one which is not an hybrid system.

  1. Neuro fuzzy system
  2. Fuzzy logic system
  3. Fuzzy genetic
  4. Neuro genetic
    

Question 18 : The number of elements in a set is called its_____.

  1. Modality
  2. Associativity
  3. Cardinality
  4. Elasticity
    

Question 19 : The interconnections of a perceptron are :

  1. Unidirectional
  2. Bidirectional
  3. Scatterred
  4. Linear
    

Question 20 : Which of the following search techniques has the capacity to overcome the problem of local optima ?

  1. Genetic algorithms
  2. Neural Network
  3. Depth First Search
  4. Fuzzy Logic
    

Question 21 : Choose the correct sequence of steps taken in designing a fuzzy logic controller.

  1. Fuzzification → Rule evaluation → Defuzzification
  2. Fuzzification → Defuzzification → Rule evaluation
  3. Rule evaluation → Fuzzification → Defuzzification
  4. Rule evaluation → Defuzzification → Fuzzification
    

Question 22 : Which of the following phenomena is not modeled by fuzzy set theory?

  1. Randomness
  2. Vagueness
  3. Uncertainty
  4. Certainty
    

Question 23 : Genetic Algorithms are inspired by____.

  1. Statistical mechanics
  2. Big bang theory
  3. Natural evolution
  4. Deployment theory
    

Question 24 : The coffee is warm.Here linguist variable warm can be represented by:

  1. Crisp Logic
  2. Boolean set theory
  3. Fuzzy logic
  4. Real Number
    

Question 25 : Characteristic features of membership functions are:

  1. Intution, Inference, Rank Ordering
  2. Fuzzy Algorithm, Neural network, Genetic Algorithm
  3. Core, Support , Boundary
  4. Weighted Average, center of Sums, Median
    
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