fuzzy interaction - definição. O que é fuzzy interaction. Significado, conceito
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O que (quem) é fuzzy interaction - definição

SYSTEM FOR REASONING ABOUT VAGUENESS
Fuzzy Logic; Fuzzy logician; Formal fuzzy logic; Fuzzy transportation; Fuzzy Transportation; Fuzzy logics; Fuzzy databases; Applications of fuzzy logic; Compensatory fuzzy logic; Fuzzy inference; Fuzzy inference system; Linguistic variable (fuzzy logic); Zadeh operator; Fuzzy Turing machine; Fuzzy database; Fuzzy relational database; Propositional fuzzy logic; Gödel fuzzy logic; Product fuzzy logic; Probability and fuzzy logic; Fuzzy logic and probability

fuzzy subset         
  • Some Key Developments in the Introduction of Fuzzy Set Concepts.<ref name="CADsurvey"/>
SETS WHOSE ELEMENTS HAVE DEGREES OF MEMBERSHIP
Fuzzy sets; Fuzzy set theory; Fuzzification; Fuzzy subset; Credibility(fuzzy); Fuzzy category; Goguen category; Fuzzy Sets; Fuzzy relation equation; Pythagorean fuzzy set; Degree of membership; Uncertain set
In fuzzy logic, a fuzzy subset F of a set S is defined by a "membership function" which gives the degree of membership of each element of S belonging to F.
Cation–pi interaction         
  • Fig. 1: Examples of π-π. CH-π, and π-cation interactions
  • Fig. 2: The Stoddart synthesis of [2]catenane
  • 275px
  • Cationic [[Acetylcholine]] binding to a [[tryptophan]] residue of the nicotinamide acetylcholine receptor via a cation–π effect.
  • quadrupole]] charge distribution.
  • Binding energy (in kcal/mol) for Na<sup>+</sup> to benzene with prototypical substituents.<ref name="electrostaticmodel" />
  • 450px
  • Cyclophane host–guest complex
  • 450px
  • Cation–π interaction in indole-3-acetic acid choline ester compared to neutral analog
  • 450px
  • Quadrupole moments of benzene and hexafluorobenzene. The polarity is inverted due to differences in electronegativity for hydrogen and fluorine relative to carbon; the inverted quadrupole moment of hexafluorobenzene is necessary for anion-pi interactions.
  • 350px
  • Calculated interaction energies of methylamonium and benzene in a variety of solvents
  • Cyclization of squalene to form hopene
NONCOVALENT MOLECULAR INTERACTION BETWEEN THE FACE OF AN ELECTRON-RICH Π SYSTEM AND AN ADJACENT CATION; EXAMPLE OF NONCOVALENT BONDING BETWEEN A MONOPOLE (CATION) AND A QUADRUPOLE (Π SYSTEM)
Cation-pi interaction; Anion-pi interaction; Anion–pi interaction; Cation-π interaction; Cation–pi interaction
Cation–π interaction is a noncovalent molecular interaction between the face of an electron-rich π system (e.g.
Cation–π interaction         
  • Fig. 1: Examples of π-π. CH-π, and π-cation interactions
  • Fig. 2: The Stoddart synthesis of [2]catenane
  • 275px
  • Cationic [[Acetylcholine]] binding to a [[tryptophan]] residue of the nicotinamide acetylcholine receptor via a cation–π effect.
  • quadrupole]] charge distribution.
  • Binding energy (in kcal/mol) for Na<sup>+</sup> to benzene with prototypical substituents.<ref name="electrostaticmodel" />
  • 450px
  • Cyclophane host–guest complex
  • 450px
  • Cation–π interaction in indole-3-acetic acid choline ester compared to neutral analog
  • 450px
  • Quadrupole moments of benzene and hexafluorobenzene. The polarity is inverted due to differences in electronegativity for hydrogen and fluorine relative to carbon; the inverted quadrupole moment of hexafluorobenzene is necessary for anion-pi interactions.
  • 350px
  • Calculated interaction energies of methylamonium and benzene in a variety of solvents
  • Cyclization of squalene to form hopene
NONCOVALENT MOLECULAR INTERACTION BETWEEN THE FACE OF AN ELECTRON-RICH Π SYSTEM AND AN ADJACENT CATION; EXAMPLE OF NONCOVALENT BONDING BETWEEN A MONOPOLE (CATION) AND A QUADRUPOLE (Π SYSTEM)
Cation-pi interaction; Anion-pi interaction; Anion–pi interaction; Cation-π interaction; Cation–pi interaction
Cation–π interaction is a noncovalent molecular interaction between the face of an electron-rich π system (e.g.

Wikipédia

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. By contrast, in Boolean logic, the truth values of variables may only be the integer values 0 or 1.

The term fuzzy logic was introduced with the 1965 proposal of fuzzy set theory by Iranian Azerbaijani mathematician Lotfi Zadeh. Fuzzy logic had, however, been studied since the 1920s, as infinite-valued logic—notably by Łukasiewicz and Tarski.

Fuzzy logic is based on the observation that people make decisions based on imprecise and non-numerical information. Fuzzy models or fuzzy sets are mathematical means of representing vagueness and imprecise information (hence the term fuzzy). These models have the capability of recognising, representing, manipulating, interpreting, and using data and information that are vague and lack certainty.

Fuzzy logic has been applied to many fields, from control theory to artificial intelligence.