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Soft Computing: Fuzzy Set Theory
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Soft Computing: Fuzzy Set Theory
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25 Questions

1. ______________ is/are the way/s to represent uncertainty.
2. A fuzzy set wherein no membership function has its value equal to 1 is called
3. What are the requirements of learning laws?
4. In a Fuzzy set a prototypical element has a value
5. Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following.
6. What are the requirements of learning laws?
7. What is asynchronous update in a network?
8. The room temperature is hot. Here the hot (use of linguistic variable is used) can be represented by _______
9. The truth values of traditional set theory is ____________ and that of fuzzy set is __________
10. The values of the set membership is represented by ___________
11. The membership functions are generally represented in
12. The membership values of the membership function are nor strictly monotonically increasing or decreasing or strictly monoronically increasing than decreasing.
13. Like relational databases there does exists fuzzy relational databases.
14. Three main basic features involved in characterizing membership function are
15. What is the form of Fuzzy logic?
16. Fuzzy Logic can be implemented in?
17. What action to take when IF (temperature=Warm) AND (target=Warm) THEN?
18. Membership function defines the fuzziness in a fuzzy set irrespective of the elements in the set, which are discrete or continuous.
19. How many main parts are there in Fuzzy Logic Systems Architecture?
20. A fuzzy set whose membership function has at least one element x in the universe whose membership value. This unity is called
21. How many output Fuzzy Logic produce?
22. Each element of X is mapped to a value between 0 and 1. It is called _____.
23. Japanese were the first to utilize fuzzy logic practically on high-speed trains in Sendai.
24. How many level of fuzzifier is there?
25. What is equilibrium in neural systems?

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