Fuzzy sets, decision making and expert systems
Fuzzy sets, decision making and expert systems
Fuzzy sets and fuzzy logic: the foundations of application—from a mathematical point of view
Fuzzy sets and fuzzy logic: the foundations of application—from a mathematical point of view
Fuzzy logic as a basis of approximate reasoning
Fuzzy logic for the management of uncertainty
Inconsistency in possibilistic knowledge bases: to live with it or not live with it
Fuzzy logic for the management of uncertainty
Use of fuzzy relations in knowledge representation, acquisition, and processing
Fuzzy logic for the management of uncertainty
Representation and use of imprecise temporal knowledge in dynamic systems
Fuzzy Sets and Systems
Logic for applications
Fuzzy Relation Equations and Their Applications to Knowledge Engineering
Fuzzy Relation Equations and Their Applications to Knowledge Engineering
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The approximate reasoning is perceived as a derivation of new formulas with the corresponding temporal attributes, within a fuzzy theory defined by the fuzzy set of special axioms. In a management application, the reasoning is evolutionary because of unexpected events which may change the state of the expert system. In this kind of situations it is necessary to elaborate certain mechanisms in order to maintain the coherence of the obtained conclusions, to figure out their degree of reliability and the time domain for which these are true. These last aspects stand as possible further directions of development at a basic logic level. The purpose of this paper is to characterize an extended fuzzy logic system with temporal attributes, attained by incorporating the basic elements of a first-degree fuzzy logic and certain elements of temporal logic.