Anzeige
Erschienen in:
2011 | OriginalPaper | Buchkapitel
A Particle Swarm Optimization Approach for the Case Retrieval Stage in CBR
verfasst von : Nabila Nouaouria, Mounir Boukadoum
Erschienen in: Research and Development in Intelligent Systems XXVII
Verlag: Springer London
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
Finding the good experiment to reuse from the case memory is the key of success in Case Based Reasoning (CBR). The paper presents a novel associative memory model to perform this task. The algorithm is founded on a Particle Swarm Optimization (PSO) approach to compute the neighborhood of a new problem. Then, direct access to the cases in the neighborhood is performed. The model was experimented on the Adult dataset, acquired from the University of California at Irvine Machine Learning Repository and compared to flat memory model for performance. The obtained results are very promising.