An SOM-based search algorithm for dynamic systems

Yi Yuan Chen, Kuu-Young Young

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The self-organizing map (SOM), as a kind of unsupervised neural network, has been applied for both static data management and dynamic data analysis. To further exploit its ability in search, in this paper, we propose an SOM-based search algorithm (SOMS) for dynamic systems, in which the SOM is employed as a searching mechanism. And, a new SOM weight updating rule is proposed to enhance the learning efficiency, which may dynamically adjust the neighborhood function for the SOM in learning system parameters. For demonstration, the proposed learning scheme is applied for continuous optimization problem and also dynamic trajectory prediction, and its effectiveness evaluated via the simulations based on using the SOM and GA, due to their resemblance in learning and searching.

Original languageEnglish
Title of host publicationProceedings of the 9th Joint Conference on Information Sciences, JCIS 2006
DOIs
StatePublished - 1 Dec 2006
Event9th Joint Conference on Information Sciences, JCIS 2006 - Taiwan, ROC, Taiwan
Duration: 8 Oct 200611 Oct 2006

Publication series

NameProceedings of the 9th Joint Conference on Information Sciences, JCIS 2006
Volume2006

Conference

Conference9th Joint Conference on Information Sciences, JCIS 2006
CountryTaiwan
CityTaiwan, ROC
Period8/10/0611/10/06

Keywords

  • Dynamic system
  • Genetic algorithm
  • Search algorithm
  • Self-organizing map

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