Anzeige
Erschienen in:
2010 | OriginalPaper | Buchkapitel
Automatic Adaptive Modeling of Fuzzy Systems Using Particle Swarm Optimization
verfasst von : Sergio Oliveira Costa Jr., Nadia Nedjah, Luiza de Macedo Mourelle
Erschienen in: Transactions on Computational Science VIII
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Fuzzy systems are currently used in many kinds of applications, such as control, for their effectiveness and efficiency. However, these characteristics depend primarily on the model yield by human experts, which may or may not be optimized for the problem at hand. Particle swarm optimization (PSO) is a technique used in complex problems, including multi-objective problems. In this paper, we propose an algorithm that can generate fuzzy systems automatically for different kinds of problems by simply providing the objective function and the problem variables. This automatic generation is performed using particle swarm optimization. To be able to do so and in order to avoid dealing with inconsistent fuzzy systems, we used some known techniques, such as the WM method, to help in developing meaningful rules and clustering concepts to generate membership functions. Tests using three three-dimensional functions have been carried out and the obtained results are presented.