doi: 10.7763/IJCTE.2014.V6.828
How Data Mining Techniques Can Improve Simulation Studies
Manel Saad Saoud
,
Abdelhak Boubetra ,
Safa Attia
- Department of Computer Science, University of Bordj Bou Arreridj, Algeria.
Abstract
Researchers take years and even decades of observation in order to analyze socio-economic phenomenon. Whereas the agent-based modeling simulation (ABMS) provides a new issue by offering the possibility to create virtual societies in which individuals and organizations are directly represented with their observed interactions. As it is known simulation generates and consumes a large amount of data. The analysis of these data which may contain implicit and hidden information will always remain a very difficult phase in the ABMS. As a solution to this problematic, the use of data mining techniques can contribute to the right analysis of the phenomena that emerges in these systems. In this paper we aim the investigation of agent-based modeling simulation and data mining techniques.
Keywords
- Agent-based modeling and simulation
- data mining
- analysis behaviors
- emergence
How to Cite
Manel Saad Saoud, Abdelhak Boubetra, and Safa Attia, "How Data Mining Techniques Can Improve Simulation Studies," International Journal of Computer Theory and Engineering, vol. 6, no. 1, pp. 15-19, 2014. https://doi.org/10.7763/IJCTE.2014.V6.828
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).