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  2. Fuzzy logic - Wikipedia

    en.wikipedia.org/wiki/Fuzzy_logic

    Fuzzy logic is a form of many-valued logic in which the truth value of variables may be any real number between 0 and 1. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false. [1]

  3. Fuzzy concept - Wikipedia

    en.wikipedia.org/wiki/Fuzzy_concept

    The basic idea of fuzzy logic is that a real number is assigned to each statement written in a language, within a range from 0 to 1, where 1 means that the statement is completely true, and 0 means that the statement is completely false, while values less than 1 but greater than 0 represent that the statement is "partly true", to a given ...

  4. Fuzzy control system - Wikipedia

    en.wikipedia.org/wiki/Fuzzy_control_system

    A fuzzy control system is a control system based on fuzzy logic –a mathematical system that analyzes analog input values in terms of logical variables that take on continuous values between 0 and 1, in contrast to classical or digital logic, which operates on discrete values of either 1 or 0 (true or false, respectively).

  5. T-norm fuzzy logics - Wikipedia

    en.wikipedia.org/wiki/T-norm_fuzzy_logics

    Basic fuzzy logic BL is the logic of (the class of) all continuous t-norms It turns out that many logics of particular t-norms and classes of t-norms are axiomatizable. The completeness theorem of the axiomatic system with respect to the corresponding t-norm semantics on [0, 1] is then called the standard completeness of the logic.

  6. Fuzzy mathematics - Wikipedia

    en.wikipedia.org/wiki/Fuzzy_mathematics

    Fuzzy mathematics is the branch of mathematics including fuzzy set theory and fuzzy logic that deals with partial inclusion of elements in a set on a spectrum, as opposed to simple binary "yes" or "no" (0 or 1) inclusion. It started in 1965 after the publication of Lotfi Asker Zadeh's seminal work Fuzzy sets. [1]

  7. Fuzzy rule - Wikipedia

    en.wikipedia.org/wiki/Fuzzy_rule

    Fuzzy rules are used within fuzzy logic systems to infer an output based on input variables. Modus ponens and modus tollens are the most important rules of inference. [1] A modus ponens rule is in the form Premise: x is A Implication: IF x is A THEN y is B Consequent: y is B. In crisp logic, the premise x is A can only be true or false

  8. Membership function (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Membership_function...

    The values between 0 and 1 characterize fuzzy members, which belong to the fuzzy set only partially. Membership function of a fuzzy set Sometimes, [ 1 ] a more general definition is used, where membership functions take values in an arbitrary fixed algebra or structure L {\displaystyle L} [ further explanation needed ] ; usually it is required ...

  9. BL (logic) - Wikipedia

    en.wikipedia.org/wiki/BL_(logic)

    In mathematical logic, basic fuzzy logic (or shortly BL), the logic of the continuous t-norms, is one of the t-norm fuzzy logics. It belongs to the broader class of substructural logics , or logics of residuated lattices ; [ 1 ] it extends the logic MTL of all left-continuous t-norms.