An SOM-Based Search Algorithm for Dynamic Systems

DOI

10.2991/jcis.2006.291How to use a DOI?

Keywords

Self-Organizing Map, Search Algorithm,Dynamic System, Genetic Algorithm.

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.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yi-Yuan Chen
AU  - Kuu-Young Young
PY  - 2006/10
DA  - 2006/10
TI  - An SOM-Based Search Algorithm for Dynamic Systems
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.291
DO  - 10.2991/jcis.2006.291
ID  - Chen2006/10
ER  -