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fuzzy logic is a logic which we have to implement in c language

I don't agree that fuzzy logic is the best approach to uncertainty

Fuzzy Logic - album - was created on 1996-05-20.

How can you describe the cup contains 500 millimeters as fuzzy logic?

The cast of Fuzzy Logic - 1998 includes: Carlos Bertoli

Crisp :Binary logicIt may be occur or non occurindicator functionFuzzy logicContinuous valued logicmembership functionConsider about degree of membership

MALABO, hndi malinaw... fuzzy logic,,, malabong lohika,,,

Certainly fuzzy logic is not the best in solving uncertainty, but..... it is on of the best alternatives to that exists to model uncertainty.

membership function is the one of the fuzzy function which is used to develope the fuzzy set value . the fuzzy logic is depends upon membership function

Fuzzy engineering is an industry term which generally refers to the design of a product that benefits from fuzzy logic. Fuzzy logic contracts with traditional digital logic in that it utilizes a weighted non-binary result making process. For example, if two sensors were connected to a fuzzy logic algorithm, each sensor might respond slightly differently from the other. Depending on which sensor produced the "best result" a weight would be assigned. That weight would then be applied as a bias and a "fuzzy" response would be produced. Fuzzy logic is of particular value in the fields of artificial intelligence, robotics, feedback loop modeling and in human mimicktry. Because fuzzy logic produces a result which is not "0" or "1" it is well suited in applications that require computational results for life's "grey areas".

It would probably be an algorithm using fuzzy logic.Traditional logic has only two possible outcomes, true or false. Fuzzy logic instead uses a graded scale with many intermediate values, like a number between 0.0 and 1.0. (Similar to what probability theory does.)A fuzzy algorithm would then use fuzzy logic to operate on inputs and give a result. Applications include control logic (controlling engine speed, for instance, where it can be handy to have some intermediate values between "full speed" and "full stop") and edge detection in images.See related link.

two cells and fuzzy turbine is to determine how to initialized the category of any other individual who use logic for immediate planning..

Fuzzy Logic stop stalking me, God!

Yes.

The Powerpuff Girls - 1998 Buttercrush Fuzzy Logic 1-4 is rated/received certificates of: Australia:G

Werner Hopf has written: 'Fuzzy logic zur Steuerung auftragsorientierter Werkstattfertigung' -- subject(s): Mathematical models, Computer integrated manufacturing systems, Industrial management, Fuzzy logic

G. Chen has written: 'Introduction to fuzzy sets, fuzzy logic, and fuzzy control systems' -- subject(s): Soft computing, Fuzzy systems 'Introduction to fuzzy systems' -- subject(s): Fuzzy systems, Fuzzy logic 'An overview of instability and fingering during immiscible fluid flow in porous and fractured media' -- subject(s): Mathematical models, Hydrogeology, Radioactive waste disposal in the ground 'From chaos to order' -- subject(s): Chaotic behavior in systems, Industrial applications

computer-based system(it contains both hard ware and software) that can process data that are incomplete or only partially correct Fuzzy logic was introduced as an artificial intelligence technique, when it was realized that normal boolean logic would not suffice. When we make intelligent decisions, we cannot limit ourselves to "true" or "false" possibilities (boolean). We have decisions like "maybe" and other shades of gray. This is what is introduced with fuzzy logic: the ability to describe degrees of truth. Example: in fuel station if you stop a fuel injecting motor at 1.55897ltrs.it can be done with the help of fuzzy logic.fuzzy has a meaning like accurate.

This theorem tells, roughly, that any mathematical system can be approximated by fuzzy logic. Hopefully this page http://sipi.usc.edu/~kosko/ helps more.

The difference between probability and fuzzy logic is clear when we consider the underlying concept that each attempts to model. Probability is concerned with the undecidability in the outcome of clearly defined and randomly occurring events, while fuzzy logic is concerned with the ambiguity or undecidability inherent in the description of the event itself. Fuzziness is often expressed as ambiguity rather than imprecision or uncertainty and remains a characteristic of perception as well as concept.

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A mathematical technique for dealing with imprecise data and problems that have many solutions rather than one. Although it is implemented in digital computers which ultimately make only yes-no decisions, fuzzy logic works with ranges of values, solving problems in a way that more resembles human logic. Fuzzy logic is used for solving problems with expert systems and real-time systems that must react to an imperfect environment of highly variable, volatile or unpredictable conditions. It "smoothes the edges" so to speak, circumventing abrupt changes in operation that could result from relying on traditional either-or and all-or-nothing logic.

Olafur Arnason has written: 'The use of fuzzy logic in strategic environmental assessment'

Probability theory deals with a events which have a range of probabilities of occurring, rather than a dichotomy of "happen" or "not happen". In a similar fashion, fuzzy logic deals with truth values that are not dichotomic: TRUE or FALSE, but have a range of intermediate values such as mostly true etc.

Please clarify.