Artificial Intelligence MCQs with Answers
Practice important Artificial Intelligence MCQs with answers and explanations.
Chapter: 39
Q1201:
Which is NOT a characteristic of biological neural networks compared to computers?
A. Distributed control
B. Fault tolerance
C. Central control
D. Adaptability
Correct Answer:
C
Chapter: 39
Q1202:
The perceptron was first developed by ________.
A. Alan Turing
B. John McCarthy
C. Marvin Minsky
D. McCulloch and Pitts
Correct Answer:
D
Chapter: 39
Q1203:
In a single perceptron, what does each input connection have that corresponds to synaptic efficacy in biological neurons?
A. Threshold
B. Weight
C. Bias
D. Output
Correct Answer:
B
Chapter: 39
Q1204:
The output of a single perceptron neuron is 1 when the weighted sum of inputs plus bias ________.
A. Equals zero
B. Is less than threshold
C. Is greater than or equal to threshold
D. Is less than zero
Correct Answer:
C
Chapter: 39
Q1205:
Changing the bias of a neuron affects the ________.
A. Rotation of decision line
B. Up or down shift of decision line
C. Number of inputs
D. Number of outputs
Correct Answer:
B
Chapter: 39
Q1206:
Changing the weight of a neuron affects the ________.
A. Rotation of the decision line
B. Number of neurons
C. Bias value
D. Threshold value
Correct Answer:
A
Chapter: 39
Q1207:
Which of the following problems can be solved by a single layer perceptron?
A. XOR gate
B. Non-linear problems
C. Linearly separable problems
D. All logical gates
Correct Answer:
C
Chapter: 39
Q1208:
The XOR problem is an example of a ________ problem in neural networks.
A. Linearly separable
B. Non-linearly separable
C. Unsolvable problem
D. Linear regression
Correct Answer:
B
Chapter: 39
Q1209:
A single perceptron can only classify patterns that are ________.
A. Non-linear
B. Linearly separable
C. Random
D. None of the above
Correct Answer:
B
Chapter: 39
Q1210:
The decision boundary created by a single perceptron in a 2D input space is a ________.
A. Straight line
B. Circle
C. Hyperbola
D. Parabola
Correct Answer:
A
Chapter: 39
Q1211:
The upper sloping line in the input space diagram for AND gate represents the ________.
A. Decision boundary
B. Weight threshold
C. Bias line
D. Output function
Correct Answer:
A
Chapter: 39
Q1212:
The output of an OR gate in a perceptron model is 0 when both inputs are ________.
A. (1,1)
B. (0,1)
C. (0,0)
D. (1,0)
Correct Answer:
C
Chapter: 39
Q1213:
Papert and Minsky's criticism of single-layer perceptrons included ________.
A. Their high speed
B. Requirement of linear separability
C. Inability to solve linear problems
D. Unlimited computational power
Correct Answer:
B
Chapter: 39
Q1214:
Which algorithm overcomes the limitations of the single layer perceptron?
A. Back-propagation algorithm
B. Gradient descent
C. Support vector machine
D. Decision tree
Correct Answer:
A
Chapter: 39
Q1215:
The brain contains approximately how many interconnected neurons?
A. 10 billion
B. 100 billion
C. 1 trillion
D. 1 billion
Correct Answer:
B
Chapter: 39
Q1216:
Each neuron is connected to about how many neighboring neurons?
A. 100
B. 1000
C. 10000
D. 1000000
Correct Answer:
B
Chapter: 39
Q1217:
The strength of output signal from a neuron is ________.
A. Variable depending on input strength
B. Always constant regardless of input
C. Dependent on number of synapses
D. Only based on bias
Correct Answer:
B
Chapter: 39
Q1218:
The small gap between neurons where signals are transmitted is called ________.
A. Synapse
B. Axon
C. Dendrite
D. Soma
Correct Answer:
A
Chapter: 39
Q1219:
Which of the following is NOT true about the axon output?
A. It has the same intensity at each terminal button
B. It varies with the input magnitude
C. It is unaffected by divisions in the axon
D. It is critical for maintaining uniformity in brain signals
Correct Answer:
B
Chapter: 39
Q1220:
Biological neurons process signals in ________.
A. Milliseconds
B. Nanoseconds
C. Seconds
D. Microseconds
Correct Answer:
A