An Oil-water Layer Recognition System Based on Composition Intelligence Computation
- 10.2991/iske.2007.2How to use a DOI?
- attribute reduction; neural network; genetic algorithm; oil-water layer recognition
In this paper, a composition intelligence computing method is suggested for an oil-water layer recognition system. The redundant condition attributes are reduced based on rough set attribute simplification algorithm so that an oil-water layer neural network recognition system can be simplified in order to improve network training speed. A local minimum problem of optimization computation of neural network is improved by a composition GA BP learning algorithm. Simulation result shows that the effect in oil-water layer recognition is improved by the composition intelligence computing method proposed here
- © 2007, 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/).
Cite this article
TY - CONF AU - Huanglin Zeng AU - Juan Li PY - 2007/10 DA - 2007/10 TI - An Oil-water Layer Recognition System Based on Composition Intelligence Computation BT - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007) PB - Atlantis Press SP - 6 EP - 9 SN - 1951-6851 UR - https://doi.org/10.2991/iske.2007.2 DO - 10.2991/iske.2007.2 ID - Zeng2007/10 ER -