A two-stage learning method to configure RBF centers and widths in dynamic environment employing immune operations

Title:

A two-stage learning method to configure RBF centers and widths in dynamic environment employing immune operations

Creator:

Ling, Xiaofeng, Gong, Xinbao, Zang , Xiaogang, and Ronghong, Jin

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:5049fd28-273d-44a5-aeed-ba48194d0da2
uuid:5049fd28-273d-44a5-aeed-ba48194d0da2
doi:10.14311/NNW.2011.21.021

Subject:

RBF neural network, dynamics problems, and immune evolutionary mechanism

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

This paper proposes an immunity-based RBF training algorithm for nonlinear dynamic problems. Exploiting the locally-tuned structure of RBF network through immunological metaphor, a two-stage learning technique is proposed to configure RBF centers and widths in the hidden layer. Inspired by affinity maturation process of immune response, immune evolutionary mechanism (IEM) with memory operations is implemented in the learning stages to dynamically fine-tune the network performance. Experiment results also demonstrate that the algorithm has reached good performance with relatively low computational efforts in dynamic environments.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2011 Volume:21 | Number:4

Harvested from:

CDK

Metadata only:

false