On-line Rule Updating System Using Evolutionary Computation for Managing Distributed Database
- https://doi.org/10.2991/jrnal.2015.2.2.2How to use a DOI?
- Genetic Network Programming, Rule Based Clustering, Cluster Optimization
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.
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- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
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 - https://doi.org/10.2991/jrnal.2015.2.2.2 ID - Wedashwara2015 ER -