1995, Vol. II, Núm. 2
http://hdl.handle.net/2099/2059
2022-09-26T15:23:03ZRemark on intuitionistic fuzzy logic and intuitionistic logic
http://hdl.handle.net/2099/2468
Remark on intuitionistic fuzzy logic and intuitionistic logic
Atanassov, Krassimir T.
It is shown that the axioms of the intuitionistic logic can be proved as theorems in the frames of the intuitionistic fuzzy logic.
2007-03-05T18:37:37ZAtanassov, Krassimir T.It is shown that the axioms of the intuitionistic logic can be proved as theorems in the frames of the intuitionistic fuzzy logic.Intuitionistic fuzzy relations (Part II) Effect of Atanassov's operators on the properties of the intuitionistic fuzzy relations
http://hdl.handle.net/2099/2467
Intuitionistic fuzzy relations (Part II) Effect of Atanassov's operators on the properties of the intuitionistic fuzzy relations
Burillo López, Pedro; Bustince Sola, Humberto Nicanor
In this paper we study the effect of Atanassov's operator on the properties of properties reflexive, symmetric, antisymmetric, perfect antisymmetric and transitive intuitionistic fuzzy relations. We finish the paper analysing the partial enclosure of the intuitionistic fuzzy relations and its effect on the conservation of the transitive property through Atanassov's operator.
2007-03-05T18:35:52ZBurillo López, PedroBustince Sola, Humberto NicanorIn this paper we study the effect of Atanassov's operator on the properties of properties reflexive, symmetric, antisymmetric, perfect antisymmetric and transitive intuitionistic fuzzy relations. We finish the paper analysing the partial enclosure of the intuitionistic fuzzy relations and its effect on the conservation of the transitive property through Atanassov's operator.A chunking mechanism in a neural system for the parallel processing of a propositional production rules
http://hdl.handle.net/2099/2466
A chunking mechanism in a neural system for the parallel processing of a propositional production rules
Burattini, E.; Pasconcino, A.; Tamburrini, G.
The problem of extracting more compact rules from a rule-based knowledge base is approached by means of a chunking mechanism implemented via a neural system. Taking advantage of the parallel processing potentialities of neural systems, the computational problem normally arising when introducing chuncking processes is overcome. Also the memory saturation effect is coped with using some sort of "forgetting" mechanism which allows the system to eliminate previously stored, but less often used chunks. Even though some connection weights are changed in the process of storing or discarding chunks, we emphasize that this neural system cannot be regarded as a "connectionist" system, since a localist semantic interpretation is adopted and no classical learning algorithm is employed.
2007-03-05T18:32:22ZBurattini, E.Pasconcino, A.Tamburrini, G.The problem of extracting more compact rules from a rule-based knowledge base is approached by means of a chunking mechanism implemented via a neural system. Taking advantage of the parallel processing potentialities of neural systems, the computational problem normally arising when introducing chuncking processes is overcome. Also the memory saturation effect is coped with using some sort of "forgetting" mechanism which allows the system to eliminate previously stored, but less often used chunks. Even though some connection weights are changed in the process of storing or discarding chunks, we emphasize that this neural system cannot be regarded as a "connectionist" system, since a localist semantic interpretation is adopted and no classical learning algorithm is employed.On a new class of distances between fuzzy numbers
http://hdl.handle.net/2099/2462
On a new class of distances between fuzzy numbers
Bertoluzza, Carlo; Corral Blanco, Norberto; Salas, Antonia
In the course of the studies on fuzzy regression analysis, we encountered the problem of introducing a distance between fuzzy numbers, which replaces the classical (x-y)² on the real line. Our proposal is to compute such a function as a suitable weighted mean of the distances between the \ac s of the fuzzy numbers. The main difficulty is concerned with the definition of the distance between intervals, since the current definitions present some disadvantages which are undesirable in our context. In this paper we describe an approach which removes such drawbacks.
2007-03-05T18:00:37ZBertoluzza, CarloCorral Blanco, NorbertoSalas, AntoniaIn the course of the studies on fuzzy regression analysis, we encountered the problem of introducing a distance between fuzzy numbers, which replaces the classical (x-y)² on the real line. Our proposal is to compute such a function as a suitable weighted mean of the distances between the \ac s of the fuzzy numbers. The main difficulty is concerned with the definition of the distance between intervals, since the current definitions present some disadvantages which are undesirable in our context. In this paper we describe an approach which removes such drawbacks.