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

Neural Network and Fuzzy Logic MCQs questions answers

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MCQ quiz on Neural Network and Fuzzy Logic multiple choice questions and answers on Neural Network and Fuzzy Logic MCQ questions on Neural Network and Fuzzy Logic objectives questions with answer test pdf for interview preparations, freshers jobs and competitive exams.

Neural Network and Fuzzy Logic Questions with Answers

1. the way/s to represent uncertainty.

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

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

4. A mouse device may be:

5. 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.

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

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

8. Chance Nodes are represented by,

9. Decision Nodes are represented by,

10. Decision Tree is

11. Decision Tree is a display of an algorithm.

12. Decision Trees can be used for Classification Tasks.

13. Different learning methods does not include

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

15. End Nodes are represented by,

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

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

18. Fuzzy logic is a form of

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

20. Fuzzy logic is usually represented as

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

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

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

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

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

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

27. How many types of random variables are available?

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

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

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

31. How the decision tree reaches its decision?

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

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

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

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

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

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

38. Natural language understanding is used in:

39. Perception involves

40. Semantic grammars

41. The first AI programming language was called:

42. The Personal Consultant is based on:

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

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

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

46. The values of the set membership is represented by

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

48. To which does the local structure is associated?

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

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


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