A perceptron is a ——————————–.
a) Feed-forward neural network
b) Back-propagation algorithm
c) Back-tracking algorithm
d) Feed Forward-backward algorithm
e) Optimal algorithm with Dynamic programming

1 Answer

Answer :

a) Feed-forward neural network

Related questions

Description : A perceptron is a ______________ a) Feed-forward neural network b) Backpropagation algorithm c) Backtracking algorithm d) Feed Forward-backward algorithm

Last Answer : a) Feed-forward neural network

Description : What is perceptron? a) a single layer feed-forward neural network with pre-processing b) an auto-associative neural network c) a double layer auto-associative neural network d) a neural network that contains feedback

Last Answer : a) a single layer feed-forward neural network with pre-processing

Description : A perceptron is: a) a single layer feed-forward neural network with pre-processing b) an auto-associative neural network c) a double layer auto-associative neural network d) a neural network that contains feedback

Last Answer : a) a single layer feed-forward neural network with pre-processing

Description : The network that involves backward links from output to the input and hidden layers is called _________ a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron

Last Answer : c) Recurrent neural network

Description : The network that involves backward links from output to the input and hidden layers is called as ____. a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron

Last Answer : c) Recurrent neural network

Description : Which algorithm is used in layered Feed forward Neural Network? (A) Back propagation algorithm (B) Binary Search (C) Both(A) & (B) (D) None of the Above

Last Answer : (A) Back propagation algorithm

Description : What is back propagation? a) It is another name given to the curvy function in the perceptron b) It is the transmission of error back through the network to adjust the inputs c) It is the ... the network to allow weights to be adjusted so that the network can learn d) None of the mentioned

Last Answer : c) It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn

Description : What is back propagation? a) It is another name given to the curvy function in the perceptron b) It is the transmission of error back through the network to adjust the inputs c) It is the ... network to allow weights to be adjusted so that the network can learn. d) None of the mentioned

Last Answer : c) It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn.

Description : Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex ... solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Last Answer : d) Because it is the simplest linearly inseparable problem that exists.

Description : Why are linearly separable problems of interest of neural network researchers? a) Because they are the only class of problem that network can solve successfully b) Because they are the only ... mathematical functions that are continue d) Because they are the only mathematical functions you can draw

Last Answer : b) Because they are the only class of problem that Perceptron can solve successfully

Description : This set of Artificial Intelligence MCQs focuses on Neural Networks - 2 . 1. Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in ... by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Last Answer : d) Because it is the simplest linearly inseparable problem that exists.

Description : What is an auto-associative network? a) a neural network that contains no loops b) a neural network that contains feedback c) a neural network that has only one loop d) a single layer feed-forward neural network with pre-processing

Last Answer : b) a neural network that contains feedback

Description : An auto-associative network is: a) a neural network that contains no loops b) a neural network that contains feedback c) a neural network that has only one loop d) a single layer feed-forward neural network with pre-processing

Last Answer : b) a neural network that contains feedback

Description : What is single layer feed forward neural network? 

Last Answer : A network with all the inputs connected directly to the outputs is called a single layer neural network or a perceptron networks.

Description : Which algorithm will work backward from the goal to solve a problem? a) Forward chaining b) Backward chaining c) Hill-climb algorithm d) None of the mentioned

Last Answer : b) Backward chaining

Description : Perceptron is A. General class of approaches to a problem. B. Performing several computations simultaneously C. Structures in a database those are statistically relevant D. Simple forerunner of modern neural networks, without hidden layers

Last Answer : D. Simple forerunner of modern neural networks, without hidden layers

Description : Which is mainly used for automated reasoning? a) Backward chaining b) Forward chaining c) Logic programming d) Parallel programming

Last Answer : c) Logic programming

Description : What is multilayer feed forward neural networks?

Last Answer : It consists of many hidden units. Each hidden unit act as a perceptron that represents a soft threshold functions in the input space. Output unit act as a soft threshold linear combination of several such functions.

Description : Three main basic features involved in characterizing membership function are A. Intution, Inference, Rank Ordering B. Fuzzy Algorithm, Neural network, Genetic Algorithm C. Core, Support , Boundary D. Weighted Average, center of Sums, Median

Last Answer : C. Core, Support , Boundary

Description : An algorithm A is admissible if ___________ a) It is not guaranteed to return an optimal solution when one exists b) It is guaranteed to return an optimal solution when one exists c) It returns more solutions, but not an optimal one d) It guarantees to return more optimal solutions

Last Answer : b) It is guaranteed to return an optimal solution when one exists

Description : A complete, local search algorithm always finds goal if one exists, an optimal algorithm always finds a global minimum/maximum. a) True b) False

Last Answer : a) True

Description : Which of the following neural networks uses supervised learning? (A) Multilayer perceptron (B) Self organizing feature map (C) Hopfield network (1) (A) only (2) (B) only (3) (A) and (B) only (4) (A) and (C) only

Last Answer : (1) (A) only

Description : Which data structure is used to give better heuristic estimates? a) Forwards state-space b) Backward state-space c) Planning graph algorithm d) None of the mentioned

Last Answer : c) Planning graph algorithm

Description : Which problem can frequently occur in backward chaining algorithm? a) Repeated states b) Incompleteness c) Complexity d) Both Repeated states & Incompleteness

Last Answer : d) Both Repeated states & Incompleteness

Description : Which algorithm are in more similar to backward chaining algorithm? a) Depth-first search algorithm b) Breadth-first search algorithm c) Hill-climbing search algorithm d) All of the mentioned

Last Answer : a) Depth-first search algorithm

Description : What will backward chaining algorithm will return? a) Additional statements b) Substitutes matching the query c) Logical statement d) All of the mentioned

Last Answer : b) Substitutes matching the query

Description : Reasoning strategies used in expert systems include ............... (A) Forward chaining, backward chaining and problem reduction (B) Forward chaining, backward chaining and boundary ... chaining, backward chaining and back propagation (D) Backward chaining, problem reduction and boundary mutation

Last Answer : (A) Forward chaining, backward chaining and problem reduction

Description : Which neural network allows feedback signal? (A) Feed forward Neural Network (B) Recurrent Neural Network (C) Both(A) & (B) (D) None of the Above

Last Answer : (B) Recurrent Neural Network

Description : A neural network in which the signal passes in only one direction is called _____ (A) Feed forward Neural Network (B) Recurrent Neural Network (C) Both(A) & (B) (D) None of the Above

Last Answer : (A) Feed forward Neural Network

Description : There are primarily two modes for an inference engine: forward chaining and backward chaining. a) True b) False

Last Answer : a) True

Description : Forward chaining systems are _____________ where as backward chaining systems are ___________ a) Goal-driven, goal-driven b) Goal-driven, data-driven c) Data-driven, goal-driven d) Data-driven, data-driven

Last Answer : c) Data-driven, goal-driven

Description : The term ___________ is used for a depth-first search that chooses values for one variable at a time and returns when a variable has no legal values left to assign. a) Forward search b) Backtrack search c) Hill algorithm d) Reverse-Down-Hill search

Last Answer : b) Backtrack search

Description : Which of the following statements is true for Branch-and-Bound search? (A) Underestimates of remaining distance may cause deviation from optimal path. (B) Overestimates can't cause right path to be ... Dynamic programming principle can be used to discard redundant partial paths. (D) All of the above

Last Answer : (C) Dynamic programming principle can be used to discard redundant partial paths.

Description : Which of the following statements is false? (A) Optimal binary search tree construction can be performed efficiently using dynamic programming. (B) Breadth-first search cannot be used to find connected components of a graph. (C) ... used to find the components of a graph. (1) A (2) B (3) C (4) D 

Last Answer : Answer: 2

Description : To overcome the need to backtrack in constraint satisfaction problem can be eliminated by ____________ a) Forward Searching b) Constraint Propagation c) Backtrack after a forward search d) Omitting the constraints and focusing only on goals

Last Answer : a) Forward Searching

Description : Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned

Last Answer : d) All of the mentioned

Description : Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise

Last Answer : a) It can explain result

Description : What is Neuro software? a) A software used to analyze neurons b) It is powerful and easy neural network

Last Answer : b) It is powerful and easy neural network

Description : Research scientists all over the world are taking steps towards building computers with circuits patterned after the complex interconnections existing among the human brain's nerve cells. What name ... ? a) Intelligent computers b) Supercomputers c) Neural network computers d) Smart computers

Last Answer : c) Neural network computers

Description : An Artificial Neural Network Is based on? a) Strong Artificial Intelligence approach b) Weak Artificial Intelligence approach c) Cognitive Artificial Intelligence approach d) Applied Artificial Intelligence approach

Last Answer : c) Cognitive Artificial Intelligence approach

Description : In artificial Neural Network interconnected processing elements are called A. nodes or neurons B. weights C. axons D. Soma

Last Answer : A. nodes or neurons

Description : Artificial neural network used for A. Pattern Recognition B. Classification C. Clustering D. All of these

Last Answer : D. All of these

Description : A Neural Network can answer A. For Loop questions B. what-if questions C. IF-The-Else Analysis Questions D.

Last Answer : B. what-if questions

Description : Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned

Last Answer : d) All of the mentioned

Description : Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise

Last Answer : a) It can explain result

Description : Neuro software is: a) A software used to analyze neurons b) It is powerful and easy neural network c) Designed to aid experts in real world d) It is software used by Neuro surgeon

Last Answer : b) It is powerful and easy neural network

Description : 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 ... b) (ii) is true c) (i) and (ii) are true d) None of the mentioned

Last Answer : c) (i) and (ii) are true

Description : What are the categories of neural network structures? 

Last Answer : i. Acyclic (or) Feed – forward networks  ii. Cyclic (or) Recurrent Networks

Description : What is the name of the function in the following statement “A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0”? a) Step function b) Heaviside function c) Logistic function d) Perceptron function

Last Answer : b) Heaviside function

Description : A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0. a) True b) False c) Sometimes – it can also output intermediate values as well d) Can’t say

Last Answer : a) True