bulanık mantık

listen to the pronunciation of bulanık mantık
Türkçe - İngilizce
fuzzy logic

This rice cooker uses fuzzy logic. - Bu pirinç ocağı bulanık mantık kullanır.

Fuzzy logic is a form of many-valued logic; it deals with reasoning that is approximate rather than fixed and exact
An extension of expert systems technology in which the rules can be expressed imprecisely
based on fuzzy-set theory, recognizes that statements are not necessarily only true or false, but also can be very unlikely or more or less certain Fuzzy logic allows computers to emulate the human reasoning process, which makes decisions based on vague or incomplete data, by assigning values of degree to all the elements of a set The use of fuzzy logic in products reduces time-to-market, lowers development costs, and improves product performance
A form of algebra employing a range of values from "true" to "false" that is used in decision-making with imprecise data, as in artificial intelligence systems. a type of logic which is used to try to make computers think like humans. Logic based on the concept of fuzzy sets, in which membership is expressed in varying probabilities or degrees of truth that is, as a continuum of values ranging from 0 (does not occur) to 1 (definitely occurs). As additional data are gathered, many fuzzy-logic systems are able to adjust the probability values assigned to different parameters. Because some such systems appear able to learn from their mistakes, they are often considered a crude form of artificial intelligence. The term and concept date from a 1965 paper by Lotfi A. Zadeh born 1921 . Fuzzy-logic systems achieved commercial application in the early 1990s. Advanced clothes-washing machines, for example, use fuzzy-logic systems to detect and adapt to patterns of water movement during a wash cycle, increasing efficiency and reducing water consumption. Other products using fuzzy logic include camcorders, microwave ovens, and dishwashers. Other applications include expert systems, self-regulating industrial controls, and computerized speech-and handwriting-recognition programs
Used by expert systems to allow users to respond by using qualitative terms such as great and OK
A conclusion reached by a computer recognising that all values are not absolutes such as yes or no, black or white etc Fuzzy logic makes calculations considering values in varying degrees between absolutes For example, a computer might recognise black and white as absolutes, yet make an evaluation based on a shade of grey, which is somewhere between
A technique for matching items that are similar For example if you are using a search engine to find pages containing references to Stephen Thomson using fuzzy logic, it might well return pages that contain Stephen Thompson, Steven Thomson and Steven Thompson as well
Fuzzy logic is designed for situations where information is inexact and traditional digital on/off decisions are not possible It divides data into vague categories such as "hot", "medium" and "cold"
Processing information that is ambiguous Fuzzy sets may overlap one another (e g something is both sweet and sour) Fuzzy logic uses the operations AND, OR and NOT
logic which as opposed to classical logic takes variable factors such as time and probability into account
An Artificial intelligence method for representing and reasoning with imprecisely specified knowledge, for example defining loose boundaries to distinguish Œlow‚ from Œhigh‚ values See also: Qualitative reasoning, Artificial intelligence
A way of dealing with uncertain information and variables that do not permit simple yes/no categorisations (e g colour) Can also be used to make decisions where uncertainty occurs
A method of reasoning that allows for partial or "fuzzy" descriptions of rules For example, the truth of a proposition such as "Company X is a medium-sized company" might vary over a range of from "completely false" to "completely true "
A type of full-text search (see Full Text Search) that allows the user to adjust the tolerance levels for how specifically to search on a given criteria Fuzzy logic searches often make use of Boolean logic to expand the tolerance of the search See Adaptive Pattern Recognition Processing
A form of logic in which variables can have degrees of truth or falsehood
a type of artificial intelligence (AI) that resembles human thinking in that it can measure imprecise or vague entities
Fuzzy logic is applied to fuzzy sets where membership in a fuzzy set is a probability, not necessarily 0 or 1 Non-fuzzy logic manipulates outcomes that are either true or false Fuzzy logic needs to be able to manipulate degrees of "maybe" in addition to true and false
THE USE OF A TEMPERATURE CONTROL ALGORITHM TO PREVENT OVERSHOOT BY LEARNING AND APPLYING THE OPTIMUM SYSTEM OPERATING CONDITIONS ACHIEVED BY RUNNING THE TEMPERATURE CONTROLLER FOR A SPECIFIED NUMBER OF CYCLES USES AN "IF-THEN" ALGORITHM, WHICH IS USEFUL IN 15-20% OF TEMPERATURE CONTROL CASES WHERE CLEAR-CUT ACTION IS NOT INDICATED AND LEARNING ACTION IS REQUIRED
is a mathematical method of handling imprecise or subjective information
Fuzzy logic provides an approach to approximate reasoning in which the rules of inference are approximate rather than exact Fuzzy logic is useful in manipulating information that is incomplete, imprecise, or unreliable Also called fuzzy set theory, fuzzy logic extends the simple Boolean operators, can express implication, and is used extensively in Artificial Intelligence (AI) programs Fuzzy logic allows computers to work more easily with phrases such as "fairly," "rarely," or "almost " It allows computers to use more than just true or false
Türkçe - Türkçe
Bulanık Mantık, 1961 yılında Lütfi Askerzade'nin yayınladığı bir makalenin sonucu oluşmuş bir mantık yapısıdır.Bulanık mantığın temeli bulanık küme ve alt kümelere dayanır. Klasik yaklaşımda bir varlık ya kümenin elemanıdır ya da değildir. Matematiksel olarak ifade edildiğinde varlık küme ile olan üyelik ilişkisi bakımından kümenin elemanı olduğunda (1) kümenin elemanı olmadığı zaman (0) değerini alır. Bulanık mantık klasik küme gösteriminin genişletilmesidir. Bulanık varlık kümesinde her bir varlığın üyelik derecesi vardır. Varlıkların üyelik derecesi, [0,1] aralığında herhangi bir değer olabilir ve üyelik fonksiyonu M(x) ile gösterilir