Description : Which of the following is true? Single layer associative neural networks do not have the ability to: (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in ... ) are true b) (ii) is true c) All of the mentioned d) None of the mentioned
Last Answer : a) (ii) and (iii) are true
Description : Which of the following is true? Single layer associative neural networks do not have the ability to: (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in a ... ) are true b) (ii) is true c) All of the mentioned d) None 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 : 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 : 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 : 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 : Which of the following is/are application(s) of Neural Network? (A) Pattern recognition (B) Mobile Computing (C) Speech reading(Lip-reading) (D) All of the Above
Last Answer : (D) All of the Above
Description : The Hadoop list includes the HBase database, the Apache Mahout ________ system, and matrix operations. a) Machine learning b) Pattern recognition c) Statistical classification d) Artificial intelligence
Last Answer : Machine learning
Description : What are the types of clustering technique?
Last Answer : i. Agglomerative clustering ii. K-means clustering
Description : K-means, self-organizing maps, hierarchical clustering are the example of _____. A. Supervised learning B. Unsupervised learning C. Machine learning D. Deep learning
Last Answer : B. Unsupervised learning
Description : Core of soft Computing is A. Fuzzy Computing, Neural Computing, Genetic Algorithms B. Fuzzy Networks and Artificial Intelligence C. Artificial Intelligence and Neural Science D. Neural Science and Genetic Science
Last Answer : D. Neural Science and Genetic Science
Description : Deep learning is a subfield of machine learning where concerned algorithms are inspired by the structured and function of the brain called _____. A. Machine learning B. Artificial neural networks C. Deep learning D. Robotics
Last Answer : B. Artificial neural networks
Description : How many types of recognition are there in artificial intelligence? a) 1 b) 2 c) 3 d) 4
Last Answer : c) 3
Description : The Face Recognition system 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 : d) Applied Artificial Intelligence approach
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 : 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 : 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.
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 : 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 : 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) Feed-forward neural network b) Backpropagation algorithm c) Backtracking algorithm d) Feed Forward-backward algorithm
Last Answer : a) Feed-forward 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 : 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 : 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 : 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
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
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 : 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
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
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
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 : What are the categories of neural network structures?
Last Answer : i. Acyclic (or) Feed – forward networks ii. Cyclic (or) Recurrent Networks
Description : What do you understand by Clustering , Classification and Regression model. -AI Class 9th
Last Answer : Regression: It predicts continuous valued output.The Regression analysis is the statistical model which is used to predict the numeric data instead of labels. It can also identify the ... very similar and points in different clusters are different. It determines grouping among unlabeled data.
Description : An Artificial Intelligence technique that allows computers to understand associations and relationships between objects and events is called _____________ a) heuristic processing b) cognitive science c) relative symbolism d) pattern matching
Last Answer : c) relative symbolism
Description : _________ is an artificial neural network with multiple hidden layers between the input and output layers? (A) Deep neural network (B) Shallow neural network (C) Both(A) & (B) (D) None of the Above
Last Answer : (A) Deep neural network
Description : _________ is a computational model based on the structure of biological neural networks? (A) Artificial Neural Network (ANN) (B) Biological Network (C) Both(A) & (B) (D) None of the Above
Last Answer : (A) Artificial Neural Network (ANN)
Description : A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. a) Decision tree b) Graphs c) Trees d) Neural Networks
Last Answer : a) Decision tree
Description : Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions
Last Answer : a) Linear Functions
Description : Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned
Description : 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 ... true b) (i) and (iii) are true c) Only (i) d) All of the mentioned
Description : 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. ... ) are true c) (i), (ii) and (iii) are true d) None of the mentioned
Last Answer : a) All of the mentioned are true
Description : Neural Networks are complex ______________with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions
Last Answer : b) Nonlinear Functions
Description : Claude Shannon described the operation of electronic switching circuits with a system of mathematical logic called _____________ a) LISP b) XLISP c) Neural networking d) Boolean algebra
Last Answer : c) Neural networking
Description : Neural Computing A. mimics human brain B. information processing paradigm C. Both (a) and (b) D. None of the above
Last Answer : C. Both (a) and (b)
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 of the following is the model used for learning? a) Decision trees b) Neural networks c) Propositional and FOL rules d) All of the mentioned
Description : Neural Networks are complex ———————–with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions e) Power Functions