| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 9653621 | Neurocomputing | 2005 | 7 Pages |
Abstract
This paper presents a modified particle swarm optimization (PSO) with simulated annealing (SA) technique. An improved PSO-based artificial neural network (ANN) is developed. The results show that the proposed SAPSO-based ANN has a better ability to escape from a local optimum and is more effective than the conventional PSO-based ANN.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yi Da, Ge Xiurun,