A fuzzy concept is a concept of which the meaningful content, value, or boundaries of application can vary considerably according to context or conditions, instead of being fixed once and for all. This generally means the concept is vague, lacking a fixed, precise meaning, without however being meaningless altogether. It has a meaning, or multiple meanings (it has different semantic associations). But these can become clearer only through further elaboration and specification, including a closer definition of the context in which they are used. Fuzzy concepts "lack clarity and are difficult to test or operationalize".
In logic, fuzzy concepts are often regarded as concepts which in their application, or formally speaking, are neither completely true or completely false, or which are partly true and partly false; they are ideas which require further elaboration, specification or qualification to understand their applicability (the conditions under which they truly make sense).
In mathematics and statistics, a fuzzy variable (such as "the temperature", "hot" or "cold") is a value which could lie in a probable range defined by quantitative limits or parameters, and can be usefully described with imprecise categories (such as "high", "medium" or "low").
In mathematics and computer science, the various gradations of applicable meaning of a fuzzy concept are conceptualized and described in terms of quantitative relationships defined by logical operators. Such an approach is sometimes called "degree-theoretic semantics" by logicians and philosophers, but the more usual term is fuzzy logic or many-valued logic. The basic idea 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 statements are "partly true", to a given, quantifiable extent. This makes its possible to analyze a distribution of statements for their truth-content, identify data patterns, make inferences and predictions, and model how processes operate.
Fuzzy reasoning (i.e. reasoning with graded concepts) has many practical uses. It is nowadays widely used in the programming of vehicle and transport electronics, household appliances, video games, language filters, robotics, and various kinds of electronic equipment used for pattern recognition, surveying and monitoring (such as radars). Fuzzy reasoning is also used in artificial intelligence and virtual intelligence research.
Read more about Fuzzy Concept: Origins and Etymology, Uncertainty, Language, Psychology, Applications, Analysis
Famous quotes containing the words fuzzy and/or concept:
“What do you think of us in fuzzy endeavor, you whose directions are sterling, whose lunge is straight?
Can you make a reason, how can you pardon us who memorize the rules and never score?”
—Gwendolyn Brooks (b. 1917)
“The concept is interesting: to see, as though reflected
In streaming windowpanes, the look of others through
Their own eyes.”
—John Ashbery (b. 1927)