Determining Membership Function of Fuzzy Logic Using Genetic Algorithm based on Max-Min Composition
| Main Authors: | Hartono, Hartono, Furqan, Mhd., Tulus, Tulus, Nababan, Erna Budhiarti |
|---|---|
| Format: | Book PeerReviewed |
| Bahasa: | eng |
| Terbitan: |
International conference on informatika and computing Universitas Sumatera Utara
, 2015
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| Subjects: | |
| Online Access: |
http://repository.uinsu.ac.id/8928/1/INTERIOR%202015-NOP.pdf http://repository.uinsu.ac.id/8928/7/14.%20Determining%20Membership%20Function%20of%20%20Fuzzy%20Logic%20Using%20Max-Min%20Composition.pdf http://repository.uinsu.ac.id/8928/8/INTERIOR%202015-1.pdf http://repository.uinsu.ac.id/8928/ |
Daftar Isi:
- Fuzzy logic is determined as a set of mathematical principles for knowledge representation based on degrees of membership rather than on crisp membership of classical binary logic. Membership function determines the performance of fuzzy logic as it relates to represent fuzzy set in a computer. In this paper we have proposed a method by using Max-Min Composition and Genetic Algorithm for determining membership function of fuzzy logic. Membership function used in this study is triangular and trapezoidal MF, which is the simplest form of Membership Function. Max-Min Composition is a method to calculate a Fuzzy Relation in Fuzzy Logic. A relation is a mathematical description of a situation where certain elements of sets are related to one another in some way. Using Max-Min Composition, we have a degree of relationship between the elements. Relations on fuzzy stating how strong the relationship between elements in fuzzy. The higher degree of relation level means the stronger the relationship between elements. Genetic algorithm is a heuristic search algorithm based on the idea of natural selection that occurs in the process of evolution and genetic operations. This algorithm perform an intelligent search for a solution and have a broad spectrum of possible sollution. We can combine the max-min composition method to get an idea of the strength of the relationship between elements. Based on the strength of that relationship we can determine the interval membership function by using a genetic algorithm.