# Neural Networks MCQs Artificial Intelligence

Neural Networks solved MCQs of Artificial Intelligence(questions and answers).

Artificial Intelligence problems are linearly divisible problems of attention of neural network researchers because they are the only?

(A). class of problem that network can solve efficiently

(B). mathematical functions that you can draw

(C). mathematical functions that are continue

(D). class of problem that Perceptron can solve successfully

(E). None of these

Which of the following is the name of the function that is used in this statement “A perceptron receives the weighted inputs and totals up, and if it increases a certain value, the value of its output will be 1, otherwise it just outputs the value of  0.

”?

(A). Step function

(B). Perceptron function

(C). Logistic function

(D). Heaviside function

(E). None of these

Which of the following is the usage of Neural Network?

(A). Sales forecasting

(B). Data validation

(C). Risk management

(D). All of these

(E). None of these

Artificial Intelligence is the XOR problem exceptionally exciting to neural network researchers because it can be?

(A). expressed in a manner that permits you to use a neural network

(B). the simplest linearly inseparable problem that exists.

(C). solved by a single layer perceptron

(D). it is a complex binary operation and it is unsolvable using neural networks

Which of the following is backpropagation?

(A). spread of error back through the network to permits weights to be adjusted

(B). spread of error back through the network to adjust the inputs

(C). can learn

(D). None of these

Neural Networks are complex functions with many parameters.  Select the exact function name.

(A). Exponential Functions

(B). Nonlinear Functions

(C). Discrete Functions

(D). Linear Functions

(E). None of these

A perceptron receives the weighted inputs and totals up, and if it increases a certain value, the value of its output will be 1, otherwise, it just outputs the value of  0.

(A). True

(B). False

(C). Occasionally, it can also output intermediary values as well

(D). None of these

Which of the following is not the guarantee of an artificial neural network?

(A). Artificial neural network  can handle noise

(B) Artificial neural network  can survive the failure of some nodes

(C). Artificial neural network has inherent parallelism

(D). Artificial neural network can explain the result

(E). None of these

If we have many perceptrons, then it can actually solve the XOR problem reasonably and we can say this due to the reason that each perceptron can partition off a linear part of the space itself, and they can then join their consequences.

(A). True, this works always, and these multiple perceptrons learn for the classification of even complex problems

(B). False, just having a solo perceptron is sufficient

(C). True, perceptrons  are able to do this but not able  to learn to do it

(D). None of these

Which of the following is the network that includes backward links from output to the input and hidden layers.

(A). Self-organizing maps

(B). Recurrent neural network

(C). Perceptrons

(D). Multi-layered perceptron

(E). None of these