2006, Vol. XIII, Núm. 2
http://hdl.handle.net/2099/3539
2024-03-29T11:20:59ZA short note on lattices allowing disjunctive reasoning
http://hdl.handle.net/2099/3669
A short note on lattices allowing disjunctive reasoning
Trillas i Gay, Enric; Renedo, Eloy; Alsina Català, Claudi
This short note shows that the scheme of disjunctive reasoning, a or b, not b : a, does not hold neither in proper ortholattices nor in proper de Morgan algebras. In both cases the scheme, once translated into the inequality b' · (a+b) ≤ a, forces the structure to be a boolean algebra.
2007-10-10T12:38:49ZTrillas i Gay, EnricRenedo, EloyAlsina Català, ClaudiThis short note shows that the scheme of disjunctive reasoning, a or b, not b : a, does not hold neither in proper ortholattices nor in proper de Morgan algebras. In both cases the scheme, once translated into the inequality b' · (a+b) ≤ a, forces the structure to be a boolean algebra.Fuzzy neural network approach to fuzzy polynomial
http://hdl.handle.net/2099/3668
Fuzzy neural network approach to fuzzy polynomial
Abbasbandy, Saeid; Otadi, M
In this paper, an architecture of fuzzy neural networks is proposed to find a real root of a dual fuzzy polynomial (if exists) by introducing a learning algorithm. We proposed a learning algorithm from the cost function for adjusting of crisp weights. According to fuzzy arithmetic, dual fuzzy polynomials can not be replaced by a fuzzy polynomials, directly. Finally, we illustrate our approach by numerical examples.
2007-10-10T12:38:25ZAbbasbandy, SaeidOtadi, MIn this paper, an architecture of fuzzy neural networks is proposed to find a real root of a dual fuzzy polynomial (if exists) by introducing a learning algorithm. We proposed a learning algorithm from the cost function for adjusting of crisp weights. According to fuzzy arithmetic, dual fuzzy polynomials can not be replaced by a fuzzy polynomials, directly. Finally, we illustrate our approach by numerical examples.A fuzzy-evolutionary seller agent for an automatic negotiation framework on e-commerce
http://hdl.handle.net/2099/3667
A fuzzy-evolutionary seller agent for an automatic negotiation framework on e-commerce
Manjacavas Ortíz, Ramón; Castro Sánchez, José Jesús; Moreno García, Juan
The business achievement via e-commerce is getting more important at the present time. E-commerce implies several activities. One of the most significant activity is the consummation of negotiations between sellers and buyers with the aim of reaching agreements. In order to automate these activities the intelligent agent software model is applied. In this work, it is proposed the design of a seller agent for negotiating in competitive frameworks, where many seller agents and a buyer agent negotiate products or services based on several properties. In that context, the aim of the seller agent will be to make offers that improve the other ones sent by other sellers and to maximize its profit. The design is based on the application of fuzzy logic and evolutional algorithms.
2007-10-10T12:38:01ZManjacavas Ortíz, RamónCastro Sánchez, José JesúsMoreno García, JuanThe business achievement via e-commerce is getting more important at the present time. E-commerce implies several activities. One of the most significant activity is the consummation of negotiations between sellers and buyers with the aim of reaching agreements. In order to automate these activities the intelligent agent software model is applied. In this work, it is proposed the design of a seller agent for negotiating in competitive frameworks, where many seller agents and a buyer agent negotiate products or services based on several properties. In that context, the aim of the seller agent will be to make offers that improve the other ones sent by other sellers and to maximize its profit. The design is based on the application of fuzzy logic and evolutional algorithms.Evolutionaty training for dynamical recurrent neural networks: an application in finantial time series prediction
http://hdl.handle.net/2099/3666
Evolutionaty training for dynamical recurrent neural networks: an application in finantial time series prediction
Delgado Calvo-Flores, Miguel; Pegalajar Jiménez, Mª Carmen; Pegalajar Cuéllar, Manuel
Theoretical and experimental studies have shown that traditional training
algorithms for Dynamical Recurrent Neural Networks may suffer of local optima solutions, due to the error propagation across the recurrence. In the last
years, many researchers have put forward different approaches to solve this
problem, most of them being based on heuristic procedures. In this paper,
the training capabilities of evolutionary techniques are studied, for Dynamical Recurrent Neural Networks. The performance of the models considered is
compared in the experimental section, in real finantial time series prediction
problems.
2007-10-10T12:36:54ZDelgado Calvo-Flores, MiguelPegalajar Jiménez, Mª CarmenPegalajar Cuéllar, ManuelTheoretical and experimental studies have shown that traditional training
algorithms for Dynamical Recurrent Neural Networks may suffer of local optima solutions, due to the error propagation across the recurrence. In the last
years, many researchers have put forward different approaches to solve this
problem, most of them being based on heuristic procedures. In this paper,
the training capabilities of evolutionary techniques are studied, for Dynamical Recurrent Neural Networks. The performance of the models considered is
compared in the experimental section, in real finantial time series prediction
problems.