Title | Neural Networks Multiple choice Questions and Answers-UGC NET computer science question paper 4 |
---|---|
Author | Achieve Pattanaik |
Course | Automobile Engineering |
Institution | Biju Patnaik University of Technology |
Pages | 8 |
File Size | 309 KB |
File Type | |
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Total Views | 125 |
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1.
Back propagation is a learning technique that adjusts weights in the neural network by propagating weight changes.
a.
Forward from source to sink
b.
Backward from sink to source
c.
Forward from source to hidden nodes
d.
Backward from sink to hidden nodes
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Answer: (b). Backward from sink to source
2.
Identify the following activation function : φ(V) = Z + (1/ 1 + exp (– x * V + Y) ), Z, X, Y are parameters
a.
Step function
b.
Ramp function
c.
Sigmoid function
d.
Gaussian function
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Answer: (c). Sigmoid function
3.
An articial neuron receives n inputs x1, x2, x3............xn with weights w1, w2, ..........wn attached to the input links. The weighted sum_________________ is computed to be passed on to a non-linear lter Φ called activation function to release the output.
a.
Σ wi
b.
Σ xi
c.
Σ wi + Σ xi
d.
Σ wi* xi
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(d).
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4.
Match the following knowledge representation techniques with their applications: List – I
List – II
(a) Frames
(i) Pictorial representation of objects, their attributes and relationships
(b) Conceptual dependencies (c) Associative networks (d) Scripts
(ii) To describe real world stereotype events
(iii) Record like structures for grouping closely related knowledge (iv) Structures and primitives to represent sentences
code: abcd a.
(iii) (iv) (i) (ii)
b.
(iii) (iv) (ii) (i)
c.
(iv) (iii) (i) (ii)
d.
(iv) (iii) (ii) (i)
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Answer: (a). (iii) (iv) (i) (ii)
5.
In propositional logic P ⇔ Q is equivalent to (Where ~ denotes NOT):
a.
~ (P ˅ Q) ˄ ~ (Q ˅ P)
b.
(~ P ˅ Q) ˄ (~ Q ˅ P)
c.
(P ˅ Q) ˄ (Q ˅ P)
d.
~ (P ˅ Q) → ~ (Q ˅ P)
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Answer: (b). (~ P ˅ Q) ˄ (~ Q ˅ P)
6.
Slots and facets are used in
a.
Semantic Networks
b.
Frames
c.
Rules
d.
All of these
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(b).
7.
A neuron with 3 inputs has the weight vector [0.2 -0.1 0.1]^T and a bias θ = 0. If the input vector is X = [0.2 0.4 0.2]^T then the total input to the neuron is:
a.
0.20
b.
1.0
c.
0.02
d.
-1.0
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8.
Which of the following neural networks uses supervised learning? (A) Multilayer perceptron (B) Self organizing feature map (C) Hopeld network
a.
(A) only
b.
(B) only
c.
(A) and (B) only
d.
(A) and (C) only
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9.
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(a).
Consider the following statements: (a) If primal (dual) problem has a nite optimal solution, then its dual (primal) problem has a nite optimal solution. (b) If primal (dual) problem has an unbounded optimum solution, then its dual (primal) has no feasible solution at all. (c) Both primal and dual problems may be infeasible. Which of the following is correct?
a.
(a) and (b) only
b.
(a) and (c) only
c.
(b) and (c) only
d.
(a), (b) and (c)
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Answer: (d). (a), (b) and (c)
10.
Consider the following statements : (a) Assignment problem can be used to minimize the cost. (b) Assignment problem is a special case of transportation problem. (c) Assignment problem requires that only one activity be assigned to each resource. Which of the following options is correct?
a.
(a) and (b) only
b.
(a) and (c) only
c.
(b) and (c) only
d.
(a), (b) and (c)
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Answer: (d). (a), (b) and (c)
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