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Ontologies as the semantic bridge between artificial intelligence and healthcare. [PDF]
Front Digit HealthAmbalavanan R +5 more
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A study on user innovative behavior of AI painting tools integrating SOR and Self-Determination theory. [PDF]
Sci RepFan L +6 more
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The Analyst, 2003
Fuzzy logic is a modeling method well suited for the control of complex and non-linear systems. This paper illustrates some of the power of fuzzy logic through a simple control example. For the analytical chemist, fuzzy logic incorporates imprecision from measurement noise as well as from linguistic process descriptions to produce operational control ...
Gordon, Hayward, Valerie, Davidson
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Fuzzy logic is a modeling method well suited for the control of complex and non-linear systems. This paper illustrates some of the power of fuzzy logic through a simple control example. For the analytical chemist, fuzzy logic incorporates imprecision from measurement noise as well as from linguistic process descriptions to produce operational control ...
Gordon, Hayward, Valerie, Davidson
openaire +2 more sources
New Mathematics and Natural Computation, 2006 Fuzzy logic is extended toward dynamic adaptation of the degree of fuzziness. The motivation is to explain the process of learning as a joint model improvement and fuzziness reduction. A learning system with fuzzy models is introduced. Initially, the system is in a highly fuzzy state of uncertain knowledge, and it dynamically evolves into a low-fuzzy ...
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IEEE Micro, 1997
We propose an architecture dedicated mainly to medium-range applications that demand computational power combined with low cost for the resulting hardware system (chip and board). Our architecture is a 16-bit processor with dedicated instructions and hardware for efficient support of fuzzy logic.
OLIVIERI, Mauro +3 more
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We propose an architecture dedicated mainly to medium-range applications that demand computational power combined with low cost for the resulting hardware system (chip and board). Our architecture is a 16-bit processor with dedicated instructions and hardware for efficient support of fuzzy logic.
OLIVIERI, Mauro +3 more
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JOINING GÖDEL AND ZADEH FUZZY LOGICS IN FUZZY DESCRIPTION LOGICS
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2012Ontologies have succeeded as a knowledge representation formalism in many domains of application. Nevertheless, they are not suitable to represent vague or imprecise information. To overcome this limitation, several extensions to classical ontologies based on fuzzy logic have been proposed.
Bobillo F +3 more
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Journal of Mathematical Sciences, 2005
An approach to the specification of discrete dynamical systems with non-quantative representation of uncertainty in their structure is developed. The main goal of the paper is to construct a logical calculus which can serve as a basis for specification languages for uncertain dynamical systems (fuzzy modal logic).
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An approach to the specification of discrete dynamical systems with non-quantative representation of uncertainty in their structure is developed. The main goal of the paper is to construct a logical calculus which can serve as a basis for specification languages for uncertain dynamical systems (fuzzy modal logic).
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Fuzzy Logic Programming and Fuzzy Control
Studia Logica, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Fuzzy logic in control systems: fuzzy logic controller. I
IEEE Transactions on Systems, Man, and Cybernetics, 1990For pt.I see ibid., vol.20, no.2, p.404-18, 1990. The basic aspects of the FLC (fuzzy logic controller) decision-making logic are examined. Several issues, including the definitions of a fuzzy implication, compositional operators, the interpretations of the sentence connectives 'and' and 'also', and fuzzy inference mechanisms, are investigated ...
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