“fuzzy logic”的概念、定义、翻译、参考文献-科学参考

fuzzy logic

Physics

A form of logic that allows for degrees of imprecision, used in artificial intelligence studies. More traditional logics deal with two truth values: ‘true’ and ‘false’. Fuzzy logics are multivalued dealing with such concepts as ‘fairly true’ and ‘more or less true’. These can be represented by numbers within a range [0,1], with the number representing the degree of truth. Fuzzy control is the application of fuzzy logic to the computer-control of processes.

Chemical Engineering

A form of logic used in the computer control of a process that allows for a degree of impression. In contrast to using truth values of ‘true’ or ‘false’, fuzzy logic uses terms such as ‘fairly true’ or ‘more or less true’. These are then represented numerically within the range of 0 to 1 depending on the level of truth.

Computer

A branch of logic designed specifically for representing knowledge and human reasoning in such a way that it is amenable to processing by computer. Thus fuzzy logic is applicable to expert systems, knowledge engineering, and artificial intelligence.
The more traditional propositional and predicate logics do not allow for degrees of imprecision, indicated by words or phrases such as fairly, very, quite possibly. Instead of truth values such as true and false it is possible to introduce a multivalued logic consisting of, for example, the values true, not true, very true, not very true, more or less true, not very false, very false, not false, and false. Alternatively an interval such as [0,1] can be introduced and the degree of truth can be represented by some real number in this range. Predicates are then functions that map not into {true, false} but into these more general domains.
Fuzzy logic is concerned with the study of sets and predicates of this kind. There emerge such concepts as fuzzy sets, fuzzy relationships, and fuzzy quantifiers.

Electronics and Electrical Engineering

A branch of logic designed to deal with common qualities that do not necessarily fit into mutually exclusive categories such as logic 1 and logic 0. Fuzzy logic provides a framework for capturing indistinctness, as opposed to the uncertainty of randomness. Instead of standard logic values of 1 and 0, fuzzy logic consists of variables that can take on real values μ,
$0 \leq μ \leq 1$
These new variables cannot be considered logical, except in the limits of 0 and 1; instead μs form part of a fuzzy variable, and the other part is an instance of the variable.
A fuzzy set F is a collection of ordered pairs:
${x, μ (x)}, 0 \leq μ (x) \leq 1$
where μ(x) is the membership of x in F. The function μ(x) may be determined arbitrarily or may be computed. For example, the fuzzy set of large real numbers might be defined by
$μ (x) = \frac{| x |}{(| x | + 1)}$
By this measure the number −7 has 0.875 membership in the set of large real numbers.
https://www.youtube.com/watch?v=P8wY6mi1vV8 A video introduction to the basics of fuzzy logic

单词	fuzzy logic
释义	fuzzy logic Physics A form of logic that allows for degrees of imprecision, used in artificial intelligence studies. More traditional logics deal with two truth values: ‘true’ and ‘false’. Fuzzy logics are multivalued dealing with such concepts as ‘fairly true’ and ‘more or less true’. These can be represented by numbers within a range [0,1], with the number representing the degree of truth. Fuzzy control is the application of fuzzy logic to the computer-control of processes. Chemical Engineering A form of logic used in the computer control of a process that allows for a degree of impression. In contrast to using truth values of ‘true’ or ‘false’, fuzzy logic uses terms such as ‘fairly true’ or ‘more or less true’. These are then represented numerically within the range of 0 to 1 depending on the level of truth. Computer A branch of logic designed specifically for representing knowledge and human reasoning in such a way that it is amenable to processing by computer. Thus fuzzy logic is applicable to expert systems, knowledge engineering, and artificial intelligence. The more traditional propositional and predicate logics do not allow for degrees of imprecision, indicated by words or phrases such as fairly, very, quite possibly. Instead of truth values such as true and false it is possible to introduce a multivalued logic consisting of, for example, the values true, not true, very true, not very true, more or less true, not very false, very false, not false, and false. Alternatively an interval such as [0,1] can be introduced and the degree of truth can be represented by some real number in this range. Predicates are then functions that map not into {true, false} but into these more general domains. Fuzzy logic is concerned with the study of sets and predicates of this kind. There emerge such concepts as fuzzy sets, fuzzy relationships, and fuzzy quantifiers. Electronics and Electrical Engineering A branch of logic designed to deal with common qualities that do not necessarily fit into mutually exclusive categories such as logic 1 and logic 0. Fuzzy logic provides a framework for capturing indistinctness, as opposed to the uncertainty of randomness. Instead of standard logic values of 1 and 0, fuzzy logic consists of variables that can take on real values μ, $0 \leq μ \leq 1$ These new variables cannot be considered logical, except in the limits of 0 and 1; instead μs form part of a fuzzy variable, and the other part is an instance of the variable. A fuzzy set F is a collection of ordered pairs: ${x, μ (x)}, 0 \leq μ (x) \leq 1$ where μ(x) is the membership of x in F. The function μ(x) may be determined arbitrarily or may be computed. For example, the fuzzy set of large real numbers might be defined by $μ (x) = \frac{\| x \|}{(\| x \| + 1)}$ By this measure the number −7 has 0.875 membership in the set of large real numbers. https://www.youtube.com/watch?v=P8wY6mi1vV8 A video introduction to the basics of fuzzy logic
随便看	constant failure-rate period constant function constant head permeameter Constantine I (the Great) (274–337) Constantinople constant(in physical laws) constant molar overflow constant of aberration constant offset constant of integration constant of proportionality constant prices constant proportions constant rate drying constant returns to scale constant-R network constants constant-separation traversing constant slope constant speed constant term constant variable constant-velocity gather constant-velocity stack constant-voltage source