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Artificial Intelligence & Soft Computing: Fuzzy Logic
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Artificial Intelligence & Soft Computing: Fuzzy Logic
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25 Questions

1. A fuzzy set wherein no membership function has its value equal to 1 is called
2. ______________ is/are the way/s to represent uncertainty.
3. There are also other operators, more linguistic in nature, called __________ that can be applied to fuzzy set theory.
4. Fuzzy logic is extension of Crisp set with an extension of handling the concept of Partial Truth.
5. What is the form of Fuzzy logic?
6. Membership function can be thought of as a technique to solve empirical problems on the basis of
7. A fuzzy set has a membership function whose membership values are strictly monotonically increasing or strictly monotonically decreasing or strictly monotonically increasing than strictly monotonically decreasing with increasing values for elements in the universe
8. How many output Fuzzy Logic produce?
9. Fuzzy Logic can be implemented in?
10. The room temperature is hot. Here the hot (use of linguistic variable is used) can be represented by _______
11. Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following.
12. Each element of X is mapped to a value between 0 and 1. It is called _____.
13. Japanese were the first to utilize fuzzy logic practically on high-speed trains in Sendai.
14. The truth values of traditional set theory is ____________ and that of fuzzy set is __________
15. Traditional set theory is also known as Crisp Set theory.
16. The room temperature is hot. Here the hot (use of linguistic variable is used) can be represented by _______
17. In a Fuzzy set a prototypical element has a value
18. How many main parts are there in Fuzzy Logic Systems Architecture?
19. Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following.
20. Three main basic features involved in characterizing membership function are
21. Membership function defines the fuzziness in a fuzzy set irrespective of the elements in the set, which are discrete or continuous.
22. A fuzzy set whose membership function has at least one element x in the universe whose membership value
i. unity is called
23. What action to take when IF (temperature=Warm) AND (target=Warm) THEN?
24. The membership functions are generally represented in
25. ____________ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic.

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