http://hdl.handle.net/2099/1817 Search the Channel search http://upcommons.upc.edu/revistes/simple-search http://hdl.handle.net/2099/2056 Title: A note on the symmetric difference in lattices<br/><br/>Authors: Renedo, Eloy; Trillas i Gay, Enric; Alsina Català, Claudi<br/><br/>Abstract: The paper introduces a definition of symmetric difference in lattices with negation, presents its general properties and studies those that are typical of ortholattices, orthomodular lattices, de Morgan and boolean algebras. http://hdl.handle.net/2099/2055 Title: A fuzzy logic approach to assembly line<br/><br/>Authors: Fonseca, Daniel J.; Elam, Matthew; Karr, Charles L.; Guest, C.L.<br/><br/>Abstract: This paper deals with the use of fuzzy set theory as a viable alternativemethod for modelling and solving the stochastic assembly line balancingproblem. Variability and uncertainty in the assembly line balancing problemhas traditionally been modelled through the use of statistical distributions.This may not be feasible in cases where no historical data exists. Fuzzy settheory allows for the consideration of the ambiguity involved in assigningprocessing and cycle times and the uncertainty contained within such timevariables. Two widely used line balancing methods, the COMSOAL andRanked Positional Weighting Technique, were modified to solve the balancingproblem with a fuzzy representation of the time variables. The paper showsthat the new fuzzy methods are capable of producing solutions similar to, andin some cases better than, those reached by the traditional methods. http://hdl.handle.net/2099/2054 Title: On the transfer principle in fuzzy theory<br/><br/>Authors: Kondo, Michiro; Dudek, Wieslaw A.<br/><br/>Abstract: We show in this paper that almost all results proved in many papers aboutfuzzy algebras can be proved uniformly and immediately by using so-called“Transfer Principle”. http://hdl.handle.net/2099/2053 Title: A heuristic forecasting model for stock decision<br/><br/>Authors: Zhang, D.; Jiang, Q.; Li, X.<br/><br/>Abstract: This paper describes a heuristic forecasting model based on neural networksfor stock decision-making. Some heuristic strategies are presented forenhancing the learning capability of neural networks and obtaining bettertrading performance. The China Shanghai Composite Index is used as casestudy. The forecasting model can forecast the buying and selling signs accordingto the result of neural network prediction. Results are comparedwith a benchmark buy-and-hold strategy. The forecasting model was foundcapable of consistently outperforming this benchmark strategy. http://hdl.handle.net/2099/2052 Title: A multistrategy approach for digital text<br/><br/>Authors: Castillo, María Dolores del; Serrano Moreno, José Ignacio<br/><br/>Abstract: The goal of the research described here is to develop a multistrategy classifier system that can be used for document categorization. The system automatically discovers classification patterns by applying several empirical learning methods to different representations for preclassified documents.The learners work in a parallel manner, where each learner carries out its own feature selection based on evolutionary techniques and then obtains a classification model. In classifying documents, the system combines the predictions of the learners by applying evolutionary techniques as well. The system relieson a modular, flexible architecture that makes no assumptions about the design of learners or the number of learners available and guarantees theindependence of the thematic domain. http://hdl.handle.net/2099/2051 Title: On the central limit theorem on IFS-events<br/><br/>Authors: Petrovicova, Jozefina; Beloslav, Riecan<br/><br/>Abstract: A probability theory on IFS-events has been constructed in [3], and axiomaticallycharacterized in [4]. Here using a general system of axioms itis shown that any probability on IFS-events can be decomposed onto twoprobabilities on a Lukasiewicz tribe, hence some known results from [5], [6]can be used also for IFS-sets. As an application of the approach a variant ofCentral limit theorem is presented