Artificial Intelligence MCQs

Page No. 58

What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ‘computational’ rates


a(i) and (ii) are true

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b(i) and (iii) are true

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cOnly (i)

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dAll of the mentioned

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View Answer All of the mentioned

Which of the following is true for neural networks? (i) The training time depends on the size of the network. (ii) Neural networks can be simulated on a conventional computer. (iii) Artificial neurons are identical in operation to biological ones.


aAll of the mentioned

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b(ii) is true

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c(i) and (ii) are true

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dNone of the mentioned

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View Answer (i) and (ii) are true

Which of the following is true? (i) On average, neural networks have higher computational rates than conventional computers. (ii) Neural networks learn by example. (iii) Neural networks mimic the way the human brain works.


aAll of the mentioned are true

✓


b(ii) and (iii) are true

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c(i), (ii) and (iii) are true

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dNone of the mentioned

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View Answer All of the mentioned are true

A 4-input neuron has weights 1, 2, 3 and 4. The transfer function is linear with the constant of proportionality being equal to 2. The inputs are 4, 10, 5 and 20 respectively. What will be the output?


a 238

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b76

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c119

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d123

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View Answer 238

What is an auto-associative network?


aa neural network that contains no loops

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ba neural network that contains feedback

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ca neural network that has only one loop

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da single layer feed-forward neural network with pre-processing

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View Answer a neural network that contains feedback

What is perceptron?


aa single layer feed-forward neural network with pre-processing

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ban auto-associative neural network

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c a double layer auto-associative neural network

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da neural network that contains feedback

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View Answer a single layer feed-forward neural network with pre-processing

A 3-input neuron is trained to output a zero when the input is 110 and a one when the input is 111. After generalization, the output will be zero when and only when the input is?


a000 or 110 or 011 or 101

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b010 or 100 or 110 or 101

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c000 or 010 or 110 or 100

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d100 or 111 or 101 or 001

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View Answer 000 or 010 or 110 or 100

Which of the following is an application of NN (Neural Network)?


aSales forecasting

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bData validation

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cRisk management

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dAll of the mentioned

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View Answer All of the mentioned

The network that involves backward links from output to the input and hidden layers is called _________


aSelf organizing maps

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bPerceptrons

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cRecurrent neural network

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dMulti layered perceptron

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View Answer Recurrent neural network

Having multiple perceptrons can actually solve the XOR problem satisfactorily: this is because each perceptron can partition off a linear part of the space itself, and they can then combine their results.


aTrue – this works always, and these multiple perceptrons learn to classify even complex problems

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bFalse – perceptrons are mathematically incapable of solving linearly inseparable functions, no matter what you do

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cTrue – perceptrons can do this but are unable to learn to do it – they have to be explicitly hand-coded

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dFalse – just having a single perceptron is enough

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View Answer True – perceptrons can do this but are unable to learn to do it – they have to be explicitly hand-coded

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