Training feedforward neural networks with dynamic particle swarm optimisation |
| |
Authors: | A S Rakitianskaia A P Engelbrecht |
| |
Institution: | 1.JINR LIT,Dubna,Russia;2.Department of Computer Science,University of Pretoria,Pretoria,South Africa |
| |
Abstract: | Particle swarm optimisation has been successfully applied to train feedforward neural networks in static environments. Many
real-world problems to which neural networks are applied are dynamic in the sense that the underlying data distribution changes
over time. In the context of classification problems, this leads to concept drift where decision boundaries may change over
time. This article investigates the applicability of dynamic particle swarm optimisation algorithms as neural network training
algorithms under the presence of concept drift. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|