Name
Abstract | ||
|---|---|---|
This paper introduces a novel hybrid algorithm to determine the parameters of radial basis function neural networks (number
of neurons, centers, width and weights) automatically. The hybrid algorithm combines the mix encoding particle swarm optimization
algorithm with the back propagation (BP) algorithm to form a hybrid learning algorithm (MPSO-BP) for training Radial Basis
Function Networks (RBFNs), which adapts to the network structure and updates its weights by choosing a special fitness function.
The proposed method is used to deal with three nonlinear problems, and the results obtained are compared with existent bibliography,
showing an improvement over the published methods. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s00521-008-0214-2 | Neural Computing and Applications |
Keywords | DocType | Volume |
particle swarm optimizationmix encoding � radial basis function neural networksself-adapt | Journal | 18 |
Issue | ISSN | Citations |
7 | 1433-3058 | 3 |
PageRank | References | Authors |
0.36 | 25 | 3 |