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

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
by

1 Answer

Answer :

D.
Neural Science and Genetic Science
by

Related questions

Conventional Artificial Intelligence is different from soft computing in the sense A. Conventional Artificial Intelligence deal with prdicate logic where as soft computing deal with fuzzy logic B. Conventional Artificial Intelligence methods are limited by symbols where as soft computing is based on empirical data C. Both (a) and (b) D. None of the above

Description : Conventional Artificial Intelligence is different from soft computing in the sense A. Conventional Artificial Intelligence deal with prdicate logic where as soft computing deal with fuzzy logic B. Conventional Artificial ... empirical data C. Both (a) and (b) D. None of the above

Last Answer : C. Both (a) and (b

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

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 

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

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

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 a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

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.

The first widely used commercial form of Artificial Intelligence (Al) is being used in many popular products like microwave ovens, automobiles and plug in circuit boards for desktop PCs. What is name of AI? A. Boolean logic B. Human logic C. Fuzzy logic D. Functional logic

Description : The first widely used commercial form of Artificial Intelligence (Al) is being used in many popular products like microwave ovens, automobiles and plug in circuit boards for desktop PCs. What is name of AI? A. Boolean logic B. Human logic C. Fuzzy logic D. Functional logic

Last Answer : C. Fuzzy logic 

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 operation to biological ones. a) All of the mentioned b) (ii) is true c) (i) and (ii) are true d) None of the mentioned

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

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

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

____________ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic. a) Fuzzy Relational DB b) Ecorithms c) Fuzzy Set d) None of the mentioned

Description : ____________ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic. a) Fuzzy Relational DB b) Ecorithms c) Fuzzy Set d) None of the mentioned

Last Answer : c) Fuzzy Set

______ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic. a) Fuzzy Relational DB b) Ecorithms c) Fuzzy Set d) None of the mentioned

Description : ______ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic. a) Fuzzy Relational DB b) Ecorithms c) Fuzzy Set d) None of the mentioned

Last Answer : c) Fuzzy Set

______________is a branch of science that deals with programing the systems in such a way that they automatically learn and improve with experience A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Description : ______________is a branch of science that deals with programing the systems in such a way that they automatically learn and improve with experience A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Last Answer : A. Machine Learning 

Which of the following(s) is/are found in Genetic Algorithms? (i) evolution (ii) selection (iii) reproduction (iv) mutation (a) i & ii only (b) i, ii & iii only (c) ii, iii & iv only

Description : Which of the following(s) is/are found in Genetic Algorithms? (i) evolution (ii) selection (iii) reproduction (iv) mutation (a) i & ii only (b) i, ii & iii only (c) ii, iii & iv only

Last Answer : (a) i & ii only

What is Genetic Algorithms?

Description : What is Genetic Algorithms?

Last Answer : Genetic Algorithm is a variant of stochastic beam search in which successor states are generated by combining two parent states, rather than by modifying a single state.

What is the field of Natural Language Processing (NLP)? a) Computer Science b) Artificial Intelligence c) Linguistics d) All of the mentioned

Description : What is the field of Natural Language Processing (NLP)? a) Computer Science b) Artificial Intelligence c) Linguistics d) All of the mentioned

Last Answer : d) All of the mentioned

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

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

Artificial intelligence is A . It uses machine-learning techniques. Here program can learn From past experience and adapt themselves to new situations B. Computational procedure that takes some value as input and produces some value as output. C. Science of making machines performs tasks that would require intelligence when performed by humans D . None of these

Description : Artificial intelligence is A . It uses machine-learning techniques. Here program can learn From past experience and adapt themselves to new situations B. Computational procedure that takes some ... performs tasks that would require intelligence when performed by humans D . None of these

Last Answer : C. Science of making machines performs tasks that would require intelligence when performed by humans

A bidirectional feedback loop links computer modelling with: a. artificial science b. heuristic processing c. human intelligence d. cognitive science

Description : A bidirectional feedback loop links computer modelling with: a. artificial science b. heuristic processing c. human intelligence d. cognitive science

Last Answer : d. cognitive science

______ is a branch of computer science which deals with helping machines finds solutions to complex problems in a more human like fashions A. Artificial Intelligence B. Internet of Things C. Embedded System D. Cyber Security

Description : ______ is a branch of computer science which deals with helping machines finds solutions to complex problems in a more human like fashions A. Artificial Intelligence B. Internet of Things C. Embedded System D. Cyber Security

Last Answer : A. Artificial Intelligence 

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

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

Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

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

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 binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

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.

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 : 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

Last Answer : d) All of the mentioned

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 picture are connected or not a) (ii) and (iii) are true b) (ii) is true c) All of the mentioned d) None of the mentioned

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

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 ‘computational’ rates a) (i) and (ii) are true b) (i) and (iii) are true c) Only (i) 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

Last Answer : d) All of the mentioned

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. a) All of the mentioned are true b) (ii) and (iii) are true c) (i), (ii) and (iii) are true d) None 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

Neural Networks are complex ______________with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

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

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

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

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 : 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

Last Answer : d) All of the mentioned

Neural Networks are complex ———————–with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions e) Power Functions

Description : Neural Networks are complex ———————–with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions e) Power Functions

Last Answer : b) Nonlinear Functions

Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

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

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 : 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

Last Answer : d) All of the mentioned

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 picture are connected or not a) (ii) and (iii) are true b) (ii) is true c) All of the mentioned d) None of the mentioned

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

Last Answer : a) (ii) and (iii) are true

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 ‘computational’ rates a) (i) and (ii) are true b) (i) and (iii) are true c) Only (i) 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

Last Answer : d) All of the mentioned

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. a) All of the mentioned are true b) (ii) and (iii) are true c) (i), (ii) and (iii) are true d) None 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

What is multilayer feed forward neural networks?

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.

What are the two functions in Neural network’s Activation functions?

Description : What are the two functions in Neural network’s Activation functions? 

Last Answer : i. Threshold function  ii. Sigmoid function

Define Neural Networks.

Description : Define Neural Networks.

Last Answer : It consists of nodes or units connected by directed links. A link propagates the activation. Each link has a numeric weight which determines the strength and sign of the connection.

Computer programs that mimic the way the human brain processes information is called as A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Description : Computer programs that mimic the way the human brain processes information is called as A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Last Answer : The correct answer is: C. Neural Networks Neural Networks are computer programs or models that are designed to mimic the way the human brain processes information. They are a subset of ... advanced form of neural networks that uses multiple layers of artificial neurons to perform complex tasks.

In ____ the goal is for the software to use what it has learned in one area to solve problems in other areas. A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Description : In ____ the goal is for the software to use what it has learned in one area to solve problems in other areas. A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Last Answer : B. Deep Learning 

Fuzzy Computing A . mimics human behaviour B. doesnt deal with 2 valued logic C. deals with information which is vague, imprecise, uncertain, ambiguous, inexact, or probabilistic D . All of the above

Description : Fuzzy Computing A . mimics human behaviour B. doesnt deal with 2 valued logic C. deals with information which is vague, imprecise, uncertain, ambiguous, inexact, or probabilistic D . All of the above

Last Answer : D . All of the above

The region of universe that is characterized by complete membership in the set is called A. Core B. Support C. Boundary D. Fuzzy

Description : The region of universe that is characterized by complete membership in the set is called A. Core B. Support C. Boundary D. Fuzzy

Last Answer : A. Core

Neural Computing A. mimics human brain B. information processing paradigm C. Both (a) and (b) D. None of the above

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)

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

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

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

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

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

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

Last Answer : D. All of these

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

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

The concept of connect intelligence is derived from: (A) virtual reality (B) fuzzy logic (C) bluetooth technology (D) value added networks

Description : The concept of connect intelligence is derived from: (A) virtual reality (B) fuzzy logic (C) bluetooth technology (D) value added networks

Last Answer : (D) value added networks

_________ 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

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)

Neurons or artificial neurons have the capability to model networks of original neurons as found in brain A. True B. False

Description : Neurons or artificial neurons have the capability to model networks of original neurons as found in brain A. True B. False

Last Answer : A. True

What of the following is considered to be a pivotal event in the history of AI. A. 1949, Donald O, The organization of Behavior. B. 1950, Computing Machinery and Intelligence. C. 1956, Dartmouth University Conference Organized by John McCarthy. D. 1961, Computer and Computer Sense. E. None of the above

Description : What of the following is considered to be a pivotal event in the history of AI. A. 1949, Donald O, The organization of Behavior. B. 1950, Computing Machinery and Intelligence. C. 1956, Dartmouth ... Conference Organized by John McCarthy. D. 1961, Computer and Computer Sense. E. None of the above

Last Answer : C. 1956, Dartmouth University Conference Organized by John McCarthy. 

The characteristics of the computer system capable of thinking, reasoning and learning are known as ____________ a) machine intelligence b) human intelligence c) artificial intelligence d) virtual intelligence

Description : The characteristics of the computer system capable of thinking, reasoning and learning are known as ____________ a) machine intelligence b) human intelligence c) artificial intelligence d) virtual intelligence

Last Answer : c) artificial intelligence