On-line Rule Updating System Using Evolutionary Computation for Managing Distributed Database

DOI

10.2991/jrnal.2015.2.2.2How to use a DOI?

Keywords

Genetic Network Programming, Rule Based Clustering, Cluster Optimization

Abstract

This research proposes a decision support system of database cluster optimization using genetic network programming (GNP) with on-line rule based clustering. GNP optimizes cluster quality by reanalyzing weak points of each cluster and maintaining rules stored in each cluster. The maintenance of rules includes: 1) adding new relevant rules; 2) moving rules between clusters; and 3) removing irrelevant rules. The simulations focus on optimizing cluster quality response against several unbalanced data growth to the data-set that is working with storage rules. The simulation results of the proposed method show its priority comparing to GNP rule based clustering without on-line optimization.

Copyright

© 2013, 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  - JOUR
AU  - Wirarama Wedashwara
AU  - Shingo Mabu
AU  - Masanao Obayashi
AU  - Takashi Kuremoto
PY  - 2015
DA  - 2015/09/01
TI  - On-line Rule Updating System Using Evolutionary Computation for Managing Distributed Database
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 73
EP  - 78
VL  - 2
IS  - 2
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2015.2.2.2
DO  - 10.2991/jrnal.2015.2.2.2
ID  - Wedashwara2015
ER  -