RT Conference Proceedings
T1 A comparison between the Pittsburgh and Michigan approaches for the binary PSO algorithm
A1 Cervantes, Alejandro
A1 Galván, Inés M.
A1 Isasi, Pedro
AB This paper shows the performance of the binary PSO algorithm as a classification system. These systems are classified in two different perspectives: the Pittsburgh and the Michigan approaches. In order to implement the Michigan approach binary PSO algorithm, the standard PSO dynamic equations are modified, introducing a repulsive force to favor particle competition. A dynamic neighborhood, adapted to classification problems, is also defined. Both classifiers are tested using a reference set of problems, where both classifiers achieve better performance than many classification techniques. The Michigan PSO classifier shows clear advantages over the Pittsburgh one both in terms of success rate and speed. The Michigan PSO can also be generalized to the continuous version of the PSO.
PB IEEE
SN 0-7803-9363-5
YR 2005
FD 2005-09
LK https://hdl.handle.net/10016/4020
UL https://hdl.handle.net/10016/4020
LA eng
NO IEEE Congress on Evolutionary Computation. Edimburgo, 5 september 2005
DS e-Archivo
RD 18 may. 2024