Лотфи Заде цитаты

Лотфи Заде — американский математик и логик, автор термина «нечёткая логика» и один из основателей теории нечётких множеств, профессор Калифорнийского университета .

Предложенная Лотфи Заде «нечёткая логика» была попыткой связать математику с интуитивным способом, которым люди разговаривают, думают и взаимодействуют с миром. Wikipedia  

✵ 4. Февраль 1921 – 6. Сентябрь 2017
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Лотфи Заде цитаты

Лотфи Заде: Цитаты на английском языке

“In general, complexity and precision bear an inverse relation to one another in the sense that, as the complexity of a problem increases, the possibility of analysing it in precise terms diminishes. Thus 'fuzzy thinking' may not be deplorable, after all, if it makes possible the solution of problems which are much too complex for precise analysis.”

Zadeh (1972) "Fuzzy languages and their relation to human intelligence". in: Proceedings of the International Conference Man and Computer, Bordeaux, France. Basel: S. Karger, pp. 130-165. cited in Gaines (1976) "Foundations of fuzzy reasoning" in: International Journal of Man-Machine Studies 8(6), p. 624
1970s

“To what degree is something true or false?”

Attributed to Zadeh in: " What is Fuzzy Logic? http://www.azer.com/aiweb/categories/magazine/24_folder/24_articles/24_fuzzywhat.html" in: Azerbaijan international Vol 2.4 (Winter 1994). p. 47
This quote is introduced as "The question Zadeh always insists upon asking".
1990s

“The question really isn't whether I'm American, Russian, Iranian, Azerbaijani, or anything else. I've been shaped by all these people and cultures and I feel quite comfortable among all of them.”

Zadeh (1994) in: Betty Blair. "Short Biographical Sketch" http://www.azer.com/aiweb/categories/magazine/24_folder/24_articles/24_zadeh.html. Azerbaijan International, Vol. 2:4 (Winter 1994), p. 49.
1990s

“A linguistic variable is a variable whose values are words or sentences in a natural or synthetic language.”

Вариант: A linguistic variable is defined as a variable whose values are sentences in a natural or artificial language.
Источник: 1970s, Outline of a new approach to the analysis of complex systems and decision processes (1973), p. 28

“It was a biologist — Ludwig von Bertalanffy — who long ago perceived the essential unity of system concepts and techniques in the various fields of science and who in writings and lectures sought to attain recognition for “general systems theory” as a distinct scientific discipline. It is pertinent to note, however, that the work of Bertalannfy and his school, being motivated primarily by problems arising in the study of biological systems, is much more empirical and qualitative in spirit than the work of those system theorists who received their training in exact sciences.
In fact, there is a fairly wide gap between what might be regarded as “animate” system theorists and “inanimate” system theorists at the present time, and it is not at all certain that this gap will be narrowed, much less closed, in the near future.
There are some who feel this gap reflects the fundamental inadequacy of the conventional mathematics—the mathematics of precisely defined points, functions, sets, probability measures, etc.—for coping with the analysis of biological systems, and that to deal effectively with such systems, we need a radically different kind of mathematics, the mathematics of fuzzy or cloudy quantities which are not describable in terms of probability distributions. Indeed the need for such mathematics is becoming increasingly apparent even in the realms of inanimate systems”

Zadeh (1962) "From circuit theory to system theory", Proceedings I.R.E., 1962, 50, 856-865. cited in: Brian R. Gaines (1979) " General systems research: quo vadis? http://pages.cpsc.ucalgary.ca/~gaines/reports/SYS/GS79/GS79.pdf", General Systems, Vol. 24 (1979), p. 12
1960s

“A frequent source of misunderstanding has to do with the interpretation of fuzzy logic. The problem is that the term fuzzy logic has two different meanings. More specifically, in a narrow sense, fuzzy logic, FLn, is a logical system which may be viewed as an extension and generalization of classical multivalued logics. But in a wider sense, fuzzy logic, FLw is almost synonymous with the theory of fuzzy sets.”

In this context, what is important to recognize is that: (a) FL<sub>w</sub> is much broader than FL<sub>n</sub> and subsumes FL<sub>n</sub> as one of its branches; (b) the agenda of FL<sub>n</sub> is very different from the agendas of classical multivalued logics; and (c) at this juncture, the term fuzzy logic is usually used in its wide rather than narrow sense, effectively equating fuzzy logic with FL<sub>w</sub>
Zadeh (1995) in Foreword of George J. Klir Fuzzy sets and fuzzy logic: theory and applications.
1990s

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