Fuzzy rule-based systems are expert systems whose performance is strongly related to the quality of their knowledge and the associated knowledge acquisition processes and thus, the design of effective learning techniques is considered a critical and major problem of these systems. Knowledge acquisition with a swarm intelligence approach is a recent learning strategy for the evolution of fuzzy rule bases founded on swarm intelligence showing improvement over classical knowledge acquisition strategies in fuzzy rule based systems such as Pittsburgh and Michigan approaches in terms of convergence behaviour and accuracy. In this work, a generalization of this method is proposed to allow the simultaneous consideration of diversely configured knowledge bases and this way to accelerate the learning process of the original algorithm. In order to test the suggested strategy, a problem of practical importance nowadays, the design of expert meta-schedulers systems for grid computing is considered. Simulations results show the fact that the suggested adaptation improves the functionality of knowledge acquisition with a swarm intelligence approach and it reduces computational effort; at the same time it keeps the quality of the canonical strategy.
Publié le : 2015-02-10
Classification:  soft computing; grid computing; artificial intelligence; expert system; scheduling,  Knowledge-based systems, fuzzy logic, optimization, evolutionary computation, grid computing
@article{cai880,
     author = {Roc\'\i o P\'erez Prado; Telecommunication Engineering Department, University of Jaen, Alfonso X el Sabio, 28 Linares, Jaen and Jos\'e Enrique Mu\~noz Exp\'osito; Telecommunication Engineering Department, University of Jaen, Alfonso X el Sabio, 28 Linares, Jaen and Sebasti\'an Garc\'\i a-Gal\'an; Telecommunication Engineering Department, University of Jaen, Alfonso X el Sabio, 28 Linares, Jaen},
     title = {Flexible Fuzzy Rule Bases Evolution with Swarm Intelligence for Meta-Scheduling in Grid Computing},
     journal = {Computing and Informatics},
     volume = {33},
     number = {3},
     year = {2015},
     language = {en},
     url = {http://dml.mathdoc.fr/item/cai880}
}
Rocío Pérez Prado; Telecommunication Engineering Department, University of Jaen, Alfonso X el Sabio, 28 Linares, Jaen; José Enrique Muñoz Expósito; Telecommunication Engineering Department, University of Jaen, Alfonso X el Sabio, 28 Linares, Jaen; Sebastián García-Galán; Telecommunication Engineering Department, University of Jaen, Alfonso X el Sabio, 28 Linares, Jaen. Flexible Fuzzy Rule Bases Evolution with Swarm Intelligence for Meta-Scheduling in Grid Computing. Computing and Informatics, Tome 33 (2015) no. 3, . http://gdmltest.u-ga.fr/item/cai880/