Clustering to train an evolving radial basis function European Conference on Artificial Intelligence

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we propose the backpropagation algorithm to train online an evolving radial basis function. Structure and parameter learning are updated at the same time in our algorithm, we do not make difference in structure learning and parameter learning. It generate groups with an online clustering. The center is updated in order to get that the center is near to the incoming data in each iteration, in this way, It does not need to generate a new rule in each iteration, i.e., it does not generate many rules and It does not need to prune the rules. We give a time varying learning rate for backpropagation training in the parameters.

Original languageEnglish
Title of host publicationProceedings of the International Symposium on Evolving Intelligent Systems - A Symposium at the AISB 2010 Convention
Pages23-25
Number of pages3
StatePublished - 2010
Event2010 International Symposium on Evolving Intelligent Systems, EIS'10, Organised in the 2010 Annual Convention of the Society for Study of Artificial Intelligence and Simulation of Behaviour, AISB'10 - Leicester, United Kingdom
Duration: 29 Mar 20101 Apr 2010

Publication series

NameProceedings of the International Symposium on Evolving Intelligent Systems - A Symposium at the AISB 2010 Convention

Conference

Conference2010 International Symposium on Evolving Intelligent Systems, EIS'10, Organised in the 2010 Annual Convention of the Society for Study of Artificial Intelligence and Simulation of Behaviour, AISB'10
Country/TerritoryUnited Kingdom
CityLeicester
Period29/03/101/04/10

Fingerprint

Dive into the research topics of 'Clustering to train an evolving radial basis function European Conference on Artificial Intelligence'. Together they form a unique fingerprint.

Cite this