Neural Network and Fuzzy Logic MCQs Quiz Multiple Choice Questions & Answers

1. ..................is/are the way/s to represent uncertainty.

1. All of the mentioned
2. Fuzzy Logic
3. Probability
4. Entropy

2. .................are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic.

1. None of the mentioned
2. Fuzzy Relational DB
3. Ecorithms
4. Fuzzy Set

3. A model of language consists of the categories which does not include

1. Structural units
2. Language units
3. Role structure of units
4. System constraints

4. A mouse device may be:

1. both b and c
2. electro-chemical
3. mechanical
4. optical

5. 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.

1. Neural Networks
2. Decision tree
3. Graphs
4. Trees

6. An expert system differs from a database program in that only an expert system:

1. expects users to draw their own conclusions
2. contains declarative knowledge
3. contains procedural knowledge
4. features the retrieval of stored information

7. Arthur Samuel is linked inextricably with a program that played:

1. football
2. checkers
3. chess
4. cricket

8. Chance Nodes are represented by,

1. Triangles
2. Disks
3. Squares
4. Circles

9. Decision Nodes are represented by,

1. Triangles
2. Disks
3. Squares
4. Circles

10. Decision Tree is

1. None of the mentioned
2. Flow-Chart
3. Structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label
4. Both a & b

11. Decision Tree is a display of an algorithm.

1. True Statement
2. False Statement

12. Decision Trees can be used for Classification Tasks.

1. True Statement
2. False Statement

13. Different learning methods does not include

1. Introduction
2. Memorization
3. Analogy
4. Deduction

14. Elementary linguistic units which are smaller than words are:

1. All of the mentioned
2. allophones
3. phonemes
4. syllables

15. End Nodes are represented by,

1. Triangles
2. Disks
3. Squares
4. Circles

16. Factors which affect the performance of learner system does not include

1. Good data structures
2. Representation scheme used
3. Training scenario
4. Type of feedback

17. From where did the new fact inferred on new iteration is derived?

1. All of the mentioned
2. Old fact
3. Narrow fact
4. New fact

18. Fuzzy logic is a form of

1. Binary set logic
2. Two-valued logic
3. Crisp set logic
4. Many-valued logic

19. Fuzzy logic is extension of Crisp set with an extension of handling the concept of Partial Truth.

1. True Statement
2. False Statement

20. Fuzzy logic is usually represented as

1. None of the mentioned
2. IF-THEN-ELSE rules
3. IF-THEN rules
4. Both a & b

21. How many conditions are available between two actions in mutex relation?

1. 4
2. 1
3. 2
4. 3

22. How many possible sources of complexity are there in forward chaining?

1. 4
2. 1
3. 2
4. 3

23. How many terms are required for building a Bayesian model?

1. 4
2. 1
3. 2
4. 3

24. How many types of informed search method are in artificial intelligence?

1. 4
2. 1
3. 2
4. 3

25. How many types of learning are available in machine learning?

1. 4
2. 1
3. 2
4. 3

26. How many types of quantification are available in artificial intelligence?

1. 4
2. 1
3. 2
4. 3

27. How many types of random variables are available?

1. 4
2. 1
3. 2
4. 3

28. How many verb tenses are there in English language?

1. 4
2. 1
3. 2
4. 3

29. How the Bayesian network can be used to answer any query?

1. All of the mentioned
2. Full distribution
3. Joint distribution
4. Partial distribution

30. How the compactness of the Bayesian network can be described?

1. All of the mentioned
2. Locally structured
3. Fully structured
4. Partial structure

31. How the decision tree reaches its decision?

1. No test
2. Single test
3. Two test
4. Sequence of test

32. How the entries in the full joint probability distribution can be calculated?

1. None of the mentioned
2. Using variables
3. Using information
4. Both a & b

33. How to eliminate the redundant rule matching attempts in the forward chaining?

1. None of the mentioned
2. Decremental forward chaining
3. Incremental forward chaining
4. Data complexity

34. In language understanding, the levels of knowledge that does not include

1. Empirical
2. Phonological
3. Syntactic
4. Semantic

35. In LISP, the atom that stands for True Statement is

1. time
2. t
3. ml
4. y

36. Japanese were the first to utilize fuzzy logic practically on high-speed trains in Sendai.

1. True Statement
2. False Statement

37. Like relational databases there does exists fuzzy relational databases.

1. True Statement
2. False Statement

38. Natural language understanding is used in:

1. All of the mentioned
2. natural language interfaces
3. natural language front ends
4. text understanding systems

39. Perception involves

1. Dancing
2. Sights, sounds, smell and touch
3. Hitting
4. Boxing

40. Semantic grammars

1. Decode syntactic information into a semantic grammar
2. Encode semantic information into a syntactic grammar
3. Decode semantic information into a syntactic grammar
4. Encode syntactic information into a semantic grammar

41. The first AI programming language was called:

1. LISP
2. BASIC
3. FORTRAN
4. IPL(Inductive logic programming)

42. The Personal Consultant is based on:

1. All of the mentioned
2. EMYCIN
3. OPS5+
4. XCON

43. The primary interactive method of communication used by humans is:

1. All of the mentioned
2. reading
3. writing
4. speaking

44. The room temperature is hot. Here the hot (use of linguistic variable is used) can be represented by................

1. Fuzzy Set
2. Crisp Set

45. The truth values of traditional set theory is...............and that of fuzzy set is.....................

1. Either 0 or 1, either 0 or 1
2. Either 0 or 1, between 0 & 1
3. Between 0 & 1, either 0 or 1
4. Between 0 & 1, between 0 & 1

46. The values of the set membership is represented by

1. Both b & c
2. Discrete Set
3. Degree of truth
4. Probabilities

47. There are also other operators, more linguistic in nature, called................that can be applied to fuzzy set theory.

1. None of the mentioned
2. Hedges
3. Lingual Variable
4. Fuzz Variable

48. To which does the local structure is associated?

1. None of the mentioned
2. Hybrid
3. Dependent
4. Linear

49. Traditional set theory is also known as Crisp Set theory.

1. True Statement
2. False Statement

50. What are present in each level of planning graph?

1. Both a & b
2. Literals
3. Actions
4. Variables