1. PART 1 From classical sets to fuzzy sets 1. Introduction 2. Crisp sets: an overview 3. Fuzzy sets: basic types 4. Fuzzy sets: basic concepts FUZZY SETS AND FUZZY LOGIC Theory and Applications

2. Introduction Crisp set: to dichotomize the individuals in some given universe of discourse into two groups: members and nonmembers. A sharp, unambiguous distinction exists between the members and nonmembers of the set.

3. Introduction Fuzzy set: to assign each individual in the universe of discourse a value representing its grade of membership in the fuzzy set. This grade corresponds to the degree to which that individual is similar to or compatible with the concept represented by the fuzzy set. We perceive fuzzy sets as having imprecise boundaries that facilitate gradual transition from membership to nonmembership and vice versa.

4. Crisp sets: an overview Universal set: The universe of discourse, containing all the possible elements of concern in each particular context from which sets can be formed, X Empty set: The set containing no members, Member (element):

5. Crisp sets: an overview Family of sets: Three methods of defining sets: list: A = {x,y,z} rule: A = {x|P(x)} characteristic function:

6. Crisp sets: an overview Subset: Proper subset: Equal sets: Power set: P Cardinality: The number of members of a finite set, |A| Relative complement:

7. Crisp sets: an overview Complement: X is the universal set Union: Intersection: Fundamental properties

8. Crisp sets: an overview

10. Partition: Nested family: Cartesian product: Relations: Subsets of Cartesian products

11. Crisp sets: an overview Convexity: Upper bound, lower bound:

12. Crisp sets: an overview Supremum, infimum: sup A: upper bound of A no smaller is an upper bound. inf A: lower bound of A no greater is an lower bound.

13. Crisp sets: an overview

14. Fuzzy sets: basic types Membership function: Fuzzy set

15. Fuzzy sets: basic types

19. Fuzzy variables: Several fuzzy sets representing linguistic concepts, such as low, medium, high, are often employed to define states of a fuzzy variable. States of fuzzy variable: Temperature within a range [a,b] is characterized as a fuzzy variable, with states being fuzzy sets very low, low, medium, etc.

20. Fuzzy sets: basic types

21. Interval-valued fuzzy sets

22. Fuzzy sets: basic types Type 2 fuzzy sets

23. Fuzzy sets: basic types Fuzzy power set: F (A), the set of all fuzzy sets that can be defined within A Type 2: A:X→ F ([0, 1]) L fuzzy sets: A:X →L where L is a set of symbols that are partially ordered. Level 2 fuzzy sets: A: F (X) →[0, 1]

24. Fuzzy sets: basic concepts Concepts of young, middle-aged, and old

25. Fuzzy sets: basic concepts Discrete approximation

26. Fuzzy sets: basic concepts

27. α-cut :

28. Fuzzy sets: basic concepts Strong α-cut:

29. Fuzzy sets: basic concepts Level set: Support: Core:

30. Fuzzy sets: basic concepts Height: Normal, subnormal: Convex fuzzy sets: is convex for all α [0, 1].

31. Fuzzy sets: basic concepts

35. Standard fuzzy set operations Standard complement: Equilibrium points: Standard intersection: Standard union:

36. Fuzzy sets: basic concepts

40. Fundamental properties Laws of contradiction and excluded middle Fuzzy set inclusion: Scalar cardinality: Degree of subsethood:

41. Fuzzy sets: basic concepts Notation of fuzzy sets: Distance:

42. Exercise 1 1.7 1.8 1.9 1.10 1.11