Konceptimi dhe realizimi i disa funksionaliteteve tȅ fuzzy logic
Başlık çevirisi mevcut değil.
- Tez No: 840543
- Danışmanlar: PROF. DR. SHKëLQİM KUKA
- Tez Türü: Yüksek Lisans
- Konular: Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol, Bilim ve Teknoloji, Computer Engineering and Computer Science and Control, Science and Technology
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2024
- Dil: Rusça
- Üniversite: The Saint Petersburg State Polytechnic University
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 51
Özet
A logic based on the two truth values TRUE and FALSE is sometimes inadequate when describing human reasoning. Fuzzy logic uses the whole interval between 0 (FALSE) and 1 (TRUE ) to describe human reasoning. As a result, fuzzy logic is being applied in rule based automatic controllers. Fuzzy logic is an extension of Boolean logic by Lotfi Zadeh in 1965 based on the theory of fuzzy sets, which is a generalization of the classical set theory. Introducing the notion of degree in the verification of a condition enables a condition to be in a state other than true or false (thus, infinite truth degrees). Fuzzy logic provides a very valuable flexibility for reasoning, which makes it possible to take into account inaccuracies and vagueness. Thus, fuzzy logic allows to build inference systems in which decisions are without discontinuities, exible and nonlinear, i.e. closer to human behavior than classical logic is. In addition, the rules of the decision matrix are expressed in natural language. In practice fuzzy logic means computation of words. Since computation with words is possible, computerized systems can be built by embedding human expertise articulated in daily language. Also called a fuzzy inference engine or fuzzy rule-base, such a system can perform approximate reasoning somewhat similar to but much more primitive than that of the human brain. Computing with words seems to be a slightly futuristic phrase today since only certain aspects of natural language can be represented by the calculus of fuzzy sets, but still fuzzy logic remains one of the most practical ways to mimic human expertise in a realistic manner. The fuzzy approach uses a premise that humans do not represent classes of objects (e.g. class of bald men, or the class of numbers which are much greater than 50 ) as fully disjoint but rather as sets in which there may be grades of membership intermediate between full membership and non-membership.
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