Expert systems, being human-oriented systems in their essence, suffer from a lack of an appropriate tool to cope with imprecision and uncertainty available in any process of knowledge acquisition. There is a general conceptual setting of fuzzy sets, especially the possibility theory in a context of knowledge processes existing in expert systems. Here we discuss technical background covering an inference mechanism realized by using fuzzy relation equations
AbstractThe management of uncertainty and imprecision is becoming more and more important in knowled...
In this paper we sketch a method to design expert systems, probabilistic in nature, by the notions o...
In this Chapter, the steps necessary to develop a fuzzy expert system (FES) from the initial model d...
Expert systems, being human-oriented systems in their essence, suffer from a lack of an appropriate ...
Some aspects of mechanisms of approximate reasoning and knowledge acquisition for rule-based expert ...
AbstractSome aspects of mechanisms of approximate reasoning and knowledge acquisition for rule-based...
: Fuzzy relation-based models for handling uncertainty (in a non-probabilistic way) in diagnosis pro...
Abstract: Inference mechanisms and interpretations of fuzzy rule bases are studied together from the...
We give a wide overview on the applications of fuzzy relation equations theory to decision-making pr...
ABSTRACT Expert systems have been intensively developed in various applications to solve problems. T...
A possibility distribution is regarded as a knowledge representation. The measure of ignorance and f...
Zadeh proposed and developed the theory of approximate reasoning in a long series of papers in the 1...
Zadeh proposed and developed the theory of approximate reasoning in a long series of papers in the 1...
It has been recognised that formal methods are useful as a modelling tool in requirements engineerin...
EditorialInternational audienceFuzzy logic is almost 40 years old and was developed largel...
AbstractThe management of uncertainty and imprecision is becoming more and more important in knowled...
In this paper we sketch a method to design expert systems, probabilistic in nature, by the notions o...
In this Chapter, the steps necessary to develop a fuzzy expert system (FES) from the initial model d...
Expert systems, being human-oriented systems in their essence, suffer from a lack of an appropriate ...
Some aspects of mechanisms of approximate reasoning and knowledge acquisition for rule-based expert ...
AbstractSome aspects of mechanisms of approximate reasoning and knowledge acquisition for rule-based...
: Fuzzy relation-based models for handling uncertainty (in a non-probabilistic way) in diagnosis pro...
Abstract: Inference mechanisms and interpretations of fuzzy rule bases are studied together from the...
We give a wide overview on the applications of fuzzy relation equations theory to decision-making pr...
ABSTRACT Expert systems have been intensively developed in various applications to solve problems. T...
A possibility distribution is regarded as a knowledge representation. The measure of ignorance and f...
Zadeh proposed and developed the theory of approximate reasoning in a long series of papers in the 1...
Zadeh proposed and developed the theory of approximate reasoning in a long series of papers in the 1...
It has been recognised that formal methods are useful as a modelling tool in requirements engineerin...
EditorialInternational audienceFuzzy logic is almost 40 years old and was developed largel...
AbstractThe management of uncertainty and imprecision is becoming more and more important in knowled...
In this paper we sketch a method to design expert systems, probabilistic in nature, by the notions o...
In this Chapter, the steps necessary to develop a fuzzy expert system (FES) from the initial model d...